| 1. Introduction | |||
| 1. Course Outline.mp4 | 58.03 MB | ||
| 1. Course Outline.srt | 7.97 KB | ||
| 2. Join Our Online Classroom!.html | 2.43 KB | ||
| 3. Exercise Meet The Community.html | 2.83 KB | ||
| 4. All Course Resources + Notebooks.html | 1.97 KB | ||
| 4.1 Zero to Mastery TensorFlow Deep Learning on GitHub.html | 114 B | ||
| 10. NLP Fundamentals in TensorFlow | |||
| 1. More Videos Coming Soon!.html | 41 B | ||
| GetFreeCourses.Co.url | 116 B | ||
| 11. Milestone Project 2 SkimLit | |||
| 1. More Videos Coming Soon!.html | 41 B | ||
| 12. Time Series fundamentals in TensorFlow | |||
| 1. More Videos Coming Soon!.html | 41 B | ||
| 13. Milestone Project 3 BitPredict | |||
| 1. More Videos Coming Soon!.html | 41 B | ||
| 14. Passing the TensorFlow Developer Certificate Exam | |||
| 1. More Videos Coming Soon!.html | 41 B | ||
| 15. Where To Go From Here | |||
| 1. Become An Alumni.html | 944 B | ||
| 2. LinkedIn Endorsements.html | 2.05 KB | ||
| 3. TensorFlow Certificate.html | 385 B | ||
| 4. Course Review.html | 176 B | ||
| 5. The Final Challenge.html | 176 B | ||
| 16. Appendix Machine Learning Primer | |||
| 1. Quick Note Upcoming Videos.html | 706 B | ||
| 10. Section Review.mp4 | 5.56 MB | ||
| 10. Section Review.srt | 2.2 KB | ||
| 2. What is Machine Learning.mp4 | 28.31 MB | ||
| 2. What is Machine Learning.srt | 8.95 KB | ||
| 3. AIMachine LearningData Science.mp4 | 19.67 MB | ||
| 3. AIMachine LearningData Science.srt | 6.45 KB | ||
| 4. Exercise Machine Learning Playground.mp4 | 42.56 MB | ||
| 4. Exercise Machine Learning Playground.srt | 8.13 KB | ||
| 4.1 httpsteachablemachine.withgoogle.com.html | 101 B | ||
| 5. How Did We Get Here.mp4 | 30.49 MB | ||
| 5. How Did We Get Here.srt | 7.34 KB | ||
| 6. Exercise YouTube Recommendation Engine.mp4 | 19.43 MB | ||
| 6. Exercise YouTube Recommendation Engine.srt | 5.61 KB | ||
| 6.1 httpsml-playground.com#.html | 88 B | ||
| 7. Types of Machine Learning.mp4 | 22.81 MB | ||
| 7. Types of Machine Learning.srt | 5.51 KB | ||
| 8. Are You Getting It Yet.html | 160 B | ||
| 9. What Is Machine Learning Round 2.mp4 | 25.51 MB | ||
| 9. What Is Machine Learning Round 2.srt | 6.25 KB | ||
| 17. Appendix Machine Learning and Data Science Framework | |||
| 1. Quick Note Upcoming Videos.html | 706 B | ||
| 10. Modelling - Picking the Model.mp4 | 23.24 MB | ||
| 10. Modelling - Picking the Model.srt | 6.23 KB | ||
| 11. Modelling - Tuning.mp4 | 15.98 MB | ||
| 11. Modelling - Tuning.srt | 5.09 KB | ||
| 12. Modelling - Comparison.mp4 | 44.86 MB | ||
| 12. Modelling - Comparison.srt | 13.32 KB | ||
| 13. Overfitting and Underfitting Definitions.html | 1.97 KB | ||
| 14. Experimentation.mp4 | 21.3 MB | ||
| 14. Experimentation.srt | 5.09 KB | ||
| 15. Tools We Will Use.mp4 | 27.34 MB | ||
| 15. Tools We Will Use.srt | 6.08 KB | ||
| 16. Optional Elements of AI.html | 975 B | ||
| 2. Section Overview.mp4 | 13.34 MB | ||
| 2. Section Overview.srt | 4.79 KB | ||
| 3. Introducing Our Framework.mp4 | 11.39 MB | ||
| 3. Introducing Our Framework.srt | 3.7 KB | ||
| 4. 6 Step Machine Learning Framework.mp4 | 23.45 MB | ||
| 4. 6 Step Machine Learning Framework.srt | 6.86 KB | ||
| 4.1 6 Step Guide.html | 147 B | ||
| 5. Types of Machine Learning Problems.mp4 | 60.46 MB | ||
| 5. Types of Machine Learning Problems.srt | 14.46 KB | ||
| 6. Types of Data.mp4 | 29.31 MB | ||
| 6. Types of Data.srt | 6.48 KB | ||
| 7. Types of Evaluation.mp4 | 17.74 MB | ||
| 7. Types of Evaluation.srt | 4.56 KB | ||
| 8. Features In Data.mp4 | 36.78 MB | ||
| 8. Features In Data.srt | 6.88 KB | ||
| 9. Modelling - Splitting Data.mp4 | 27.55 MB | ||
| 9. Modelling - Splitting Data.srt | 7.79 KB | ||
| 18. Appendix Pandas for Data Analysis | |||
| 1. Quick Note Upcoming Videos.html | 706 B | ||
| 10. Manipulating Data.mp4 | 105 MB | ||
| 10. Manipulating Data.srt | 18.56 KB | ||
| 10.1 car-sales-missing-data.csv | 287 B | ||
| 10.2 httpsjakevdp.github.ioPythonDataScienceHandbook03.00-introduction-to-pandas.html.html | 146 B | ||
| 11. Manipulating Data 2.mp4 | 86.56 MB | ||
| 11. Manipulating Data 2.srt | 14.82 KB | ||
| 11.1 pandas-anatomy-of-a-dataframe.png | 333.24 KB | ||
| 12. Manipulating Data 3.mp4 | 91.07 MB | ||
| 12. Manipulating Data 3.srt | 14 KB | ||
| 12.1 Pandas video notes.html | 185 B | ||
| 12.2 Pandas video code.html | 191 B | ||
| 13. Assignment Pandas Practice.html | 2.05 KB | ||
| 14. How To Download The Course Assignments.mp4 | 66.79 MB | ||
| 14. How To Download The Course Assignments.srt | 11.24 KB | ||
| 14.1 Course Notes.html | 108 B | ||
| 14.2 httpscolab.research.google.com.html | 95 B | ||
| 2. Section Overview.mp4 | 10.87 MB | ||
| 2. Section Overview.srt | 3.69 KB | ||
| 3. Downloading Workbooks and Assignments.html | 967 B | ||
| 4. Pandas Introduction.mp4 | 27.46 MB | ||
| 4. Pandas Introduction.srt | 6.91 KB | ||
| 4.1 10 Minutes to pandas.html | 127 B | ||
| 4.2 Intro to pandas code.html | 191 B | ||
| 4.3 Intro to pandas notes.html | 185 B | ||
| 5. Series, Data Frames and CSVs.mp4 | 95.43 MB | ||
| 5. Series, Data Frames and CSVs.srt | 18.45 KB | ||
| 5.1 pandas-anatomy-of-a-dataframe.png | 333.24 KB | ||
| 6. Data from URLs.html | 1.09 KB | ||
| 7. Describing Data with Pandas.mp4 | 75.65 MB | ||
| 7. Describing Data with Pandas.srt | 14.22 KB | ||
| 8. Selecting and Viewing Data with Pandas.mp4 | 72.29 MB | ||
| 8. Selecting and Viewing Data with Pandas.srt | 15.22 KB | ||
| 8.1 car-sales.csv | 369 B | ||
| 9. Selecting and Viewing Data with Pandas Part 2.mp4 | 106.49 MB | ||
| 9. Selecting and Viewing Data with Pandas Part 2.srt | 18.95 KB | ||
| 19. Appendix NumPy | |||
| 1. Quick Note Upcoming Videos.html | 706 B | ||
| 10. Manipulating Arrays 2.mp4 | 67.91 MB | ||
| 10. Manipulating Arrays 2.srt | 12.01 KB | ||
| 10.1 httpswww.mathsisfun.comdatastandard-deviation.html.html | 116 B | ||
| 11. Standard Deviation and Variance.mp4 | 51.13 MB | ||
| 11. Standard Deviation and Variance.srt | 9.81 KB | ||
| 11.1 httpswww.mathsisfun.comdatastandard-deviation.html.html | 116 B | ||
| 12. Reshape and Transpose.mp4 | 53.57 MB | ||
| 12. Reshape and Transpose.srt | 9.68 KB | ||
| 13. Dot Product vs Element Wise.mp4 | 83.8 MB | ||
| 13. Dot Product vs Element Wise.srt | 15.89 KB | ||
| 13.1 httpswww.mathsisfun.comalgebramatrix-multiplying.html.html | 119 B | ||
| 14. Exercise Nut Butter Store Sales.mp4 | 91.27 MB | ||
| 14. Exercise Nut Butter Store Sales.srt | 17.41 KB | ||
| 15. Comparison Operators.mp4 | 26.38 MB | ||
| 15. Comparison Operators.srt | 5.22 KB | ||
| 16. Sorting Arrays.mp4 | 32.82 MB | ||
| 16. Sorting Arrays.srt | 8.95 KB | ||
| 17. Turn Images Into NumPy Arrays.mp4 | 85.98 MB | ||
| 17. Turn Images Into NumPy Arrays.srt | 10.6 KB | ||
| 17.1 numpy-images.zip | 7.27 MB | ||
| 17.2 NumPy Video code.html | 190 B | ||
| 17.3 Section Notes.html | 184 B | ||
| 18. Assignment NumPy Practice.html | 2.17 KB | ||
| 19. Optional Extra NumPy resources.html | 1.02 KB | ||
| 2. Section Overview.mp4 | 13.36 MB | ||
| 2. Section Overview.srt | 3.24 KB | ||
| 3. NumPy Introduction.mp4 | 26.86 MB | ||
| 3. NumPy Introduction.srt | 7.6 KB | ||
| 3.1 httpsnumpy.orgdoc.html | 83 B | ||
| 3.2 NumPy Video code.html | 190 B | ||
| 3.3 NumPy Notes.html | 184 B | ||
| 4. Quick Note Correction In Next Video.html | 1.25 KB | ||
| 5. NumPy DataTypes and Attributes.mp4 | 78.97 MB | ||
| 5. NumPy DataTypes and Attributes.srt | 20.04 KB | ||
| 6. Creating NumPy Arrays.mp4 | 66.84 MB | ||
| 6. Creating NumPy Arrays.srt | 12.45 KB | ||
| 7. NumPy Random Seed.mp4 | 51.95 MB | ||
| 7. NumPy Random Seed.srt | 10.44 KB | ||
| 8. Viewing Arrays and Matrices.mp4 | 70.66 MB | ||
| 8. Viewing Arrays and Matrices.srt | 13.86 KB | ||
| 9. Manipulating Arrays.mp4 | 80.67 MB | ||
| 9. Manipulating Arrays.srt | 17.14 KB | ||
| 9.1 httpswww.mathsisfun.comdatastandard-deviation.html.html | 116 B | ||
| 2. Deep Learning and TensorFlow Fundamentals | |||
| 1. What is deep learning.mp4 | 34.17 MB | ||
| 1. What is deep learning.srt | 6.8 KB | ||
| 1.1 All course materials and links!.html | 114 B | ||
| 10. Creating your first tensors with TensorFlow and tf.constant().mp4 | 134.83 MB | ||
| 10. Creating your first tensors with TensorFlow and tf.constant().srt | 24.75 KB | ||
| 11. Creating tensors with TensorFlow and tf.Variable().mp4 | 70.85 MB | ||
| 11. Creating tensors with TensorFlow and tf.Variable().srt | 9.9 KB | ||
| 12. Creating random tensors with TensorFlow.mp4 | 88.45 MB | ||
| 12. Creating random tensors with TensorFlow.srt | 13.03 KB | ||
| 13. Shuffling the order of tensors.mp4 | 89.86 MB | ||
| 13. Shuffling the order of tensors.srt | 12.63 KB | ||
| 14. Creating tensors from NumPy arrays.mp4 | 101.34 MB | ||
| 14. Creating tensors from NumPy arrays.srt | 15.03 KB | ||
| 15. Getting information from your tensors (tensor attributes).mp4 | 87.39 MB | ||
| 15. Getting information from your tensors (tensor attributes).srt | 16.96 KB | ||
| 16. Indexing and expanding tensors.mp4 | 86.57 MB | ||
| 16. Indexing and expanding tensors.srt | 16.96 KB | ||
| 17. Manipulating tensors with basic operations.mp4 | 45.22 MB | ||
| 17. Manipulating tensors with basic operations.srt | 6.95 KB | ||
| 18. Matrix multiplication with tensors part 1.mp4 | 100.85 MB | ||
| 18. Matrix multiplication with tensors part 1.srt | 15.22 KB | ||
| 19. Matrix multiplication with tensors part 2.mp4 | 107.79 MB | ||
| 19. Matrix multiplication with tensors part 2.srt | 17.35 KB | ||
| 2. Why use deep learning.mp4 | 62.32 MB | ||
| 2. Why use deep learning.srt | 14.19 KB | ||
| 20. Matrix multiplication with tensors part 3.mp4 | 80.62 MB | ||
| 20. Matrix multiplication with tensors part 3.srt | 13.27 KB | ||
| 21. Changing the datatype of tensors.mp4 | 71.39 MB | ||
| 21. Changing the datatype of tensors.srt | 8.64 KB | ||
| 22. Tensor aggregation (finding the min, max, mean & more).mp4 | 89.58 MB | ||
| 22. Tensor aggregation (finding the min, max, mean & more).srt | 12.88 KB | ||
| 23. Tensor troubleshooting example (updating tensor datatypes).mp4 | 69.39 MB | ||
| 23. Tensor troubleshooting example (updating tensor datatypes).srt | 6.63 KB | ||
| 24. Finding the positional minimum and maximum of a tensor (argmin and argmax).mp4 | 96.5 MB | ||
| 24. Finding the positional minimum and maximum of a tensor (argmin and argmax).srt | 12.38 KB | ||
| 25. Squeezing a tensor (removing all 1-dimension axes).mp4 | 30.2 MB | ||
| 25. Squeezing a tensor (removing all 1-dimension axes).srt | 3.84 KB | ||
| 26. One-hot encoding tensors.mp4 | 59.73 MB | ||
| 26. One-hot encoding tensors.srt | 7.98 KB | ||
| 27. Trying out more tensor math operations.mp4 | 55.93 MB | ||
| 27. Trying out more tensor math operations.srt | 6.23 KB | ||
| 28. Exploring TensorFlow and NumPy's compatibility.mp4 | 43.75 MB | ||
| 28. Exploring TensorFlow and NumPy's compatibility.srt | 7.11 KB | ||
| 29. Making sure our tensor operations run really fast on GPUs.mp4 | 110.91 MB | ||
| 29. Making sure our tensor operations run really fast on GPUs.srt | 14.45 KB | ||
| 3. What are neural networks.mp4 | 63.43 MB | ||
| 3. What are neural networks.srt | 14.7 KB | ||
| 30. TensorFlow Fundamentals challenge, exercises & extra-curriculum.html | 1.95 KB | ||
| 31. Python + Machine Learning Monthly.html | 796 B | ||
| 32. LinkedIn Endorsements.html | 2.05 KB | ||
| 4. What is deep learning already being used for.mp4 | 76.21 MB | ||
| 4. What is deep learning already being used for.srt | 13.48 KB | ||
| 5. What is and why use TensorFlow.mp4 | 69.16 MB | ||
| 5. What is and why use TensorFlow.srt | 11.74 KB | ||
| 6. What is a Tensor.mp4 | 27.58 MB | ||
| 6. What is a Tensor.srt | 4.99 KB | ||
| 7. What we're going to cover throughout the course.mp4 | 29.38 MB | ||
| 7. What we're going to cover throughout the course.srt | 7.23 KB | ||
| 8. How to approach this course.mp4 | 26.18 MB | ||
| 8. How to approach this course.srt | 8.24 KB | ||
| 9. Need A Refresher.html | 942 B | ||
| 20. BONUS SECTION | |||
| 1. Special Bonus Lecture.html | 3.65 KB | ||
| 3. Neural network regression with TensorFlow | |||
| 1. Introduction to Neural Network Regression with TensorFlow.mp4 | 60.06 MB | ||
| 1. Introduction to Neural Network Regression with TensorFlow.srt | 11.41 KB | ||
| 1.1 All course materials and links (notebooks, code, data, slides) on GitHub.html | 114 B | ||
| 10. Evaluating a TensorFlow model part 2 (the three datasets).mp4 | 81.56 MB | ||
| 10. Evaluating a TensorFlow model part 2 (the three datasets).srt | 14.05 KB | ||
| 11. Evaluating a TensorFlow model part 3 (getting a model summary).mp4 | 192.79 MB | ||
| 11. Evaluating a TensorFlow model part 3 (getting a model summary).srt | 21.53 KB | ||
| 12. Evaluating a TensorFlow model part 4 (visualising a model's layers).mp4 | 70.28 MB | ||
| 12. Evaluating a TensorFlow model part 4 (visualising a model's layers).srt | 9.23 KB | ||
| 13. Evaluating a TensorFlow model part 5 (visualising a model's predictions).mp4 | 78.88 MB | ||
| 13. Evaluating a TensorFlow model part 5 (visualising a model's predictions).srt | 11.92 KB | ||
| 14. Evaluating a TensorFlow model part 6 (common regression evaluation metrics).mp4 | 70.37 MB | ||
| 14. Evaluating a TensorFlow model part 6 (common regression evaluation metrics).srt | 11.16 KB | ||
| 15. Evaluating a TensorFlow regression model part 7 (mean absolute error).mp4 | 56.09 MB | ||
| 15. Evaluating a TensorFlow regression model part 7 (mean absolute error).srt | 8.1 KB | ||
| 16. Evaluating a TensorFlow regression model part 7 (mean square error).mp4 | 32.31 MB | ||
| 16. Evaluating a TensorFlow regression model part 7 (mean square error).srt | 3.88 KB | ||
| 17. Setting up TensorFlow modelling experiments part 1 (start with a simple model).mp4 | 127.26 MB | ||
| 17. Setting up TensorFlow modelling experiments part 1 (start with a simple model).srt | 17.44 KB | ||
| 18. Setting up TensorFlow modelling experiments part 2 (increasing complexity).mp4 | 95.63 MB | ||
| 18. Setting up TensorFlow modelling experiments part 2 (increasing complexity).srt | 15.86 KB | ||
| 19. Comparing and tracking your TensorFlow modelling experiments.mp4 | 92.25 MB | ||
| 19. Comparing and tracking your TensorFlow modelling experiments.srt | 13.18 KB | ||
| 2. Inputs and outputs of a neural network regression model.mp4 | 57.57 MB | ||
| 2. Inputs and outputs of a neural network regression model.srt | 13.12 KB | ||
| 20. How to save a TensorFlow model.mp4 | 92.29 MB | ||
| 20. How to save a TensorFlow model.srt | 11.39 KB | ||
| 21. How to load and use a saved TensorFlow model.mp4 | 104.37 MB | ||
| 21. How to load and use a saved TensorFlow model.srt | 12.81 KB | ||
| 22. (Optional) How to save and download files from Google Colab.mp4 | 67.7 MB | ||
| 22. (Optional) How to save and download files from Google Colab.srt | 7.79 KB | ||
| 23. Putting together what we've learned part 1 (preparing a dataset).mp4 | 143.51 MB | ||
| 23. Putting together what we've learned part 1 (preparing a dataset).srt | 18.7 KB | ||
| 24. Putting together what we've learned part 2 (building a regression model).mp4 | 121.38 MB | ||
| 24. Putting together what we've learned part 2 (building a regression model).srt | 17.95 KB | ||
| 25. Putting together what we've learned part 3 (improving our regression model).mp4 | 155.11 MB | ||
| 25. Putting together what we've learned part 3 (improving our regression model).srt | 18.8 KB | ||
| 26. Preprocessing data with feature scaling part 1 (what is feature scaling).mp4 | 92.51 MB | ||
| 26. Preprocessing data with feature scaling part 1 (what is feature scaling).srt | 13.88 KB | ||
| 27. Preprocessing data with feature scaling part 2 (normalising our data).mp4 | 97.18 MB | ||
| 27. Preprocessing data with feature scaling part 2 (normalising our data).srt | 13.93 KB | ||
| 28. Preprocessing data with feature scaling part 3 (fitting a model on scaled data).mp4 | 75.72 MB | ||
| 28. Preprocessing data with feature scaling part 3 (fitting a model on scaled data).srt | 10.97 KB | ||
| 29. TensorFlow Regression challenge, exercises & extra-curriculum.html | 1.98 KB | ||
| 3. Anatomy and architecture of a neural network regression model.mp4 | 59 MB | ||
| 3. Anatomy and architecture of a neural network regression model.srt | 12.25 KB | ||
| 4. Creating sample regression data (so we can model it).mp4 | 90.16 MB | ||
| 4. Creating sample regression data (so we can model it).srt | 16.12 KB | ||
| 5. The major steps in modelling with TensorFlow.mp4 | 181.81 MB | ||
| 5. The major steps in modelling with TensorFlow.srt | 25.74 KB | ||
| 6. Steps in improving a model with TensorFlow part 1.mp4 | 45.82 MB | ||
| 6. Steps in improving a model with TensorFlow part 1.srt | 7.62 KB | ||
| 7. Steps in improving a model with TensorFlow part 2.mp4 | 90.23 MB | ||
| 7. Steps in improving a model with TensorFlow part 2.srt | 13.12 KB | ||
| 8. Steps in improving a model with TensorFlow part 3.mp4 | 132.94 MB | ||
| 8. Steps in improving a model with TensorFlow part 3.srt | 16.84 KB | ||
| 9. Evaluating a TensorFlow model part 1 (visualise, visualise, visualise).mp4 | 66.94 MB | ||
| 9. Evaluating a TensorFlow model part 1 (visualise, visualise, visualise).srt | 9.77 KB | ||
| 4. Neural network classification in TensorFlow | |||
| 1. Introduction to neural network classification in TensorFlow.mp4 | 72.81 MB | ||
| 1. Introduction to neural network classification in TensorFlow.srt | 12.76 KB | ||
| 1.1 All course materials and links (notebooks, code, data, slides) on GitHub.html | 119 B | ||
| 10. Make our poor classification model work for a regression dataset.mp4 | 123.01 MB | ||
| 10. Make our poor classification model work for a regression dataset.srt | 16.33 KB | ||
| 11. Non-linearity part 1 Straight lines and non-straight lines.mp4 | 95.62 MB | ||
| 11. Non-linearity part 1 Straight lines and non-straight lines.srt | 13.79 KB | ||
| 12. Non-linearity part 2 Building our first neural network with non-linearity.mp4 | 59 MB | ||
| 12. Non-linearity part 2 Building our first neural network with non-linearity.srt | 7.58 KB | ||
| 13. Non-linearity part 3 Upgrading our non-linear model with more layers.mp4 | 123.24 MB | ||
| 13. Non-linearity part 3 Upgrading our non-linear model with more layers.srt | 14.34 KB | ||
| 14. Non-linearity part 4 Modelling our non-linear data once and for all.mp4 | 96.62 MB | ||
| 14. Non-linearity part 4 Modelling our non-linear data once and for all.srt | 11.99 KB | ||
| 15. Non-linearity part 5 Replicating non-linear activation functions from scratch.mp4 | 146.61 MB | ||
| 15. Non-linearity part 5 Replicating non-linear activation functions from scratch.srt | 18.28 KB | ||
| 16. Getting great results in less time by tweaking the learning rate.mp4 | 136.78 MB | ||
| 16. Getting great results in less time by tweaking the learning rate.srt | 19.38 KB | ||
| 17. Using the TensorFlow History object to plot a model's loss curves.mp4 | 62.12 MB | ||
| 17. Using the TensorFlow History object to plot a model's loss curves.srt | 8.38 KB | ||
| 18. Using callbacks to find a model's ideal learning rate.mp4 | 155.88 MB | ||
| 18. Using callbacks to find a model's ideal learning rate.srt | 24.87 KB | ||
| 19. Training and evaluating a model with an ideal learning rate.mp4 | 89.01 MB | ||
| 19. Training and evaluating a model with an ideal learning rate.srt | 11.87 KB | ||
| 2. Example classification problems (and their inputs and outputs).mp4 | 50.71 MB | ||
| 2. Example classification problems (and their inputs and outputs).srt | 9.89 KB | ||
| 20. Introducing more classification evaluation methods.mp4 | 42.21 MB | ||
| 20. Introducing more classification evaluation methods.srt | 8.87 KB | ||
| 21. Finding the accuracy of our classification model.mp4 | 34.07 MB | ||
| 21. Finding the accuracy of our classification model.srt | 5.63 KB | ||
| 22. Creating our first confusion matrix (to see where our model is getting confused).mp4 | 65.7 MB | ||
| 22. Creating our first confusion matrix (to see where our model is getting confused).srt | 11.54 KB | ||
| 23. Making our confusion matrix prettier.mp4 | 114.12 MB | ||
| 23. Making our confusion matrix prettier.srt | 18.28 KB | ||
| 24. Putting things together with multi-class classification part 1 Getting the data.mp4 | 87.22 MB | ||
| 24. Putting things together with multi-class classification part 1 Getting the data.srt | 13.77 KB | ||
| 25. Multi-class classification part 2 Becoming one with the data.mp4 | 48.65 MB | ||
| 25. Multi-class classification part 2 Becoming one with the data.srt | 9.99 KB | ||
| 26. Multi-class classification part 3 Building a multi-class classification model.mp4 | 142.8 MB | ||
| 26. Multi-class classification part 3 Building a multi-class classification model.srt | 21.13 KB | ||
| 27. Multi-class classification part 4 Improving performance with normalisation.mp4 | 113.41 MB | ||
| 27. Multi-class classification part 4 Improving performance with normalisation.srt | 16.21 KB | ||
| 28. Multi-class classification part 5 Comparing normalised and non-normalised data.mp4 | 26.77 MB | ||
| 28. Multi-class classification part 5 Comparing normalised and non-normalised data.srt | 5.44 KB | ||
| 29. Multi-class classification part 6 Finding the ideal learning rate.mp4 | 73.34 MB | ||
| 29. Multi-class classification part 6 Finding the ideal learning rate.srt | 14.91 KB | ||
| 3. Input and output tensors of classification problems.mp4 | 51.01 MB | ||
| 3. Input and output tensors of classification problems.srt | 8.85 KB | ||
| 30. Multi-class classification part 7 Evaluating our model.mp4 | 119.14 MB | ||
| 30. Multi-class classification part 7 Evaluating our model.srt | 16.96 KB | ||
| 31. Multi-class classification part 8 Creating a confusion matrix.mp4 | 40.52 MB | ||
| 31. Multi-class classification part 8 Creating a confusion matrix.srt | 6.67 KB | ||
| 32. Multi-class classification part 9 Visualising random model predictions.mp4 | 65.68 MB | ||
| 32. Multi-class classification part 9 Visualising random model predictions.srt | 13.52 KB | ||
| 33. What patterns is our model learning.mp4 | 127.96 MB | ||
| 33. What patterns is our model learning.srt | 20.83 KB | ||
| 34. TensorFlow classification challenge, exercises & extra-curriculum.html | 2.48 KB | ||
| 4. Typical architecture of neural network classification models with TensorFlow.mp4 | 112.73 MB | ||
| 4. Typical architecture of neural network classification models with TensorFlow.srt | 14.61 KB | ||
| 5. Creating and viewing classification data to model.mp4 | 106.08 MB | ||
| 5. Creating and viewing classification data to model.srt | 14.39 KB | ||
| 6. Checking the input and output shapes of our classification data.mp4 | 38.15 MB | ||
| 6. Checking the input and output shapes of our classification data.srt | 6.57 KB | ||
| 7. Building a not very good classification model with TensorFlow.mp4 | 125.29 MB | ||
| 7. Building a not very good classification model with TensorFlow.srt | 16.03 KB | ||
| 8. Trying to improve our not very good classification model.mp4 | 84.29 MB | ||
| 8. Trying to improve our not very good classification model.srt | 12.67 KB | ||
| 9. Creating a function to view our model's not so good predictions.mp4 | 160.55 MB | ||
| 9. Creating a function to view our model's not so good predictions.srt | 18.99 KB | ||
| 5. Computer Vision and Convolutional Neural Networks in TensorFlow | |||
| 1. Introduction to Computer Vision with TensorFlow.mp4 | 75.01 MB | ||
| 1. Introduction to Computer Vision with TensorFlow.srt | 15 KB | ||
| 10. Improving our non-CNN model by adding more layers.mp4 | 106.47 MB | ||
| 10. Improving our non-CNN model by adding more layers.srt | 13.98 KB | ||
| 11. Breaking our CNN model down part 1 Becoming one with the data.mp4 | 90.92 MB | ||
| 11. Breaking our CNN model down part 1 Becoming one with the data.srt | 13 KB | ||
| 12. Breaking our CNN model down part 2 Preparing to load our data.mp4 | 109.48 MB | ||
| 12. Breaking our CNN model down part 2 Preparing to load our data.srt | 16.51 KB | ||
| 14. Breaking our CNN model down part 4 Building a baseline CNN model.mp4 | 85.3 MB | ||
| 14. Breaking our CNN model down part 4 Building a baseline CNN model.srt | 11.22 KB | ||
| 15. Breaking our CNN model down part 5 Looking inside a Conv2D layer.mp4 | 186.04 MB | ||
| 15. Breaking our CNN model down part 5 Looking inside a Conv2D layer.srt | 22.79 KB | ||
| 15.1 CNN Explainer website.html | 102 B | ||
| 2. Introduction to Convolutional Neural Networks (CNNs) with TensorFlow.mp4 | 76.65 MB | ||
| 2. Introduction to Convolutional Neural Networks (CNNs) with TensorFlow.srt | 12.11 KB | ||
| 20. Breaking our CNN model down part 10 Visualizing our augmented data.mp4 | 157.62 MB | ||
| 20. Breaking our CNN model down part 10 Visualizing our augmented data.srt | 21.55 KB | ||
| 24. Downloading a custom image to make predictions on.mp4 | 53.08 MB | ||
| 24. Downloading a custom image to make predictions on.srt | 6.93 KB | ||
| 25. Writing a helper function to load and preprocessing custom images.mp4 | 105.15 MB | ||
| 25. Writing a helper function to load and preprocessing custom images.srt | 13.73 KB | ||
| 26. Making a prediction on a custom image with our trained CNN.mp4 | 99.9 MB | ||
| 26. Making a prediction on a custom image with our trained CNN.srt | 15.46 KB | ||
| 27. Multi-class CNN's part 1 Becoming one with the data.mp4 | 140.19 MB | ||
| 27. Multi-class CNN's part 1 Becoming one with the data.srt | 22.69 KB | ||
| 28. Multi-class CNN's part 2 Preparing our data (turning it into tensors).mp4 | 72.72 MB | ||
| 28. Multi-class CNN's part 2 Preparing our data (turning it into tensors).srt | 9.95 KB | ||
| 29. Multi-class CNN's part 3 Building a multi-class CNN model.mp4 | 89.24 MB | ||
| 29. Multi-class CNN's part 3 Building a multi-class CNN model.srt | 10.65 KB | ||
| 3. Downloading an image dataset for our first Food Vision model.mp4 | 72.94 MB | ||
| 3. Downloading an image dataset for our first Food Vision model.srt | 10.31 KB | ||
| 30. Multi-class CNN's part 4 Fitting a multi-class CNN model to the data.mp4 | 59.66 MB | ||
| 30. Multi-class CNN's part 4 Fitting a multi-class CNN model to the data.srt | 8.96 KB | ||
| 31. Multi-class CNN's part 5 Evaluating our multi-class CNN model.mp4 | 41.05 MB | ||
| 31. Multi-class CNN's part 5 Evaluating our multi-class CNN model.srt | 6.79 KB | ||
| 32. Multi-class CNN's part 6 Trying to fix overfitting by removing layers.mp4 | 129.83 MB | ||
| 32. Multi-class CNN's part 6 Trying to fix overfitting by removing layers.srt | 16.43 KB | ||
| 34. Multi-class CNN's part 8 Things you could do to improve your CNN model.mp4 | 43.29 MB | ||
| 34. Multi-class CNN's part 8 Things you could do to improve your CNN model.srt | 6.18 KB | ||
| 36. Saving and loading our trained CNN model.mp4 | 69.28 MB | ||
| 36. Saving and loading our trained CNN model.srt | 9.07 KB | ||
| 4. Becoming One With Data.mp4 | 45.61 MB | ||
| 4. Becoming One With Data.srt | 6.72 KB | ||
| 5. Becoming One With Data Part 2.mp4 | 104.59 MB | ||
| 5. Becoming One With Data Part 2.srt | 16.06 KB | ||
| 6. Becoming One With Data Part 3.mp4 | 39.89 MB | ||
| 6. Becoming One With Data Part 3.srt | 6.54 KB | ||
| 7. Building an end to end CNN Model.mp4 | 155.09 MB | ||
| 7. Building an end to end CNN Model.srt | 26 KB | ||
| 8. Using a GPU to run our CNN model 5x faster.mp4 | 114.94 MB | ||
| 8. Using a GPU to run our CNN model 5x faster.srt | 13.05 KB | ||
| 9. Trying a non-CNN model on our image data.mp4 | 100.56 MB | ||
| 9. Trying a non-CNN model on our image data.srt | 11.63 KB | ||
| 6. Transfer Learning in TensorFlow Part 1 Feature extraction | |||
| 1. What is and why use transfer learning.mp4 | 65.81 MB | ||
| 1. What is and why use transfer learning.srt | 15.94 KB | ||
| 1.1 All course materials and links (notebooks, code, data, slides) on GitHub.html | 114 B | ||
| 10. Comparing Our Model's Results.mp4 | 143.93 MB | ||
| 10. Comparing Our Model's Results.srt | 21.56 KB | ||
| 11. TensorFlow Transfer Learning Part 1 challenge, exercises & extra-curriculum.html | 2.44 KB | ||
| 2. Downloading and preparing data for our first transfer learning model.mp4 | 132.67 MB | ||
| 2. Downloading and preparing data for our first transfer learning model.srt | 18.11 KB | ||
| 3. Introducing Callbacks in TensorFlow and making a callback to track our models.mp4 | 94.89 MB | ||
| 3. Introducing Callbacks in TensorFlow and making a callback to track our models.srt | 14.26 KB | ||
| 4. Exploring the TensorFlow Hub website for pretrained models.mp4 | 102.96 MB | ||
| 4. Exploring the TensorFlow Hub website for pretrained models.srt | 14.67 KB | ||
| 5. Building and compiling a TensorFlow Hub feature extraction model.mp4 | 135.63 MB | ||
| 5. Building and compiling a TensorFlow Hub feature extraction model.srt | 18.91 KB | ||
| 6. Blowing our previous models out of the water with transfer learning.mp4 | 99.46 MB | ||
| 6. Blowing our previous models out of the water with transfer learning.srt | 13.66 KB | ||
| 7. Plotting the loss curves of our ResNet feature extraction model.mp4 | 62.09 MB | ||
| 7. Plotting the loss curves of our ResNet feature extraction model.srt | 10.81 KB | ||
| 8. Building and training a pre-trained EfficientNet model on our data.mp4 | 105.93 MB | ||
| 8. Building and training a pre-trained EfficientNet model on our data.srt | 14.27 KB | ||
| 9. Different Types of Transfer Learning.mp4 | 110.57 MB | ||
| 9. Different Types of Transfer Learning.srt | 15.67 KB | ||
| GetFreeCourses.Co.url | 116 B | ||
| 7. Transfer Learning in TensorFlow Part 2 Fine tuning | |||
| 1. Introduction to Transfer Learning in TensorFlow Part 2 Fine-tuning.mp4 | 61.46 MB | ||
| 1. Introduction to Transfer Learning in TensorFlow Part 2 Fine-tuning.srt | 9.78 KB | ||
| 10. Downloading and preparing the data for Model 1 (1 percent of training data).mp4 | 97.8 MB | ||
| 10. Downloading and preparing the data for Model 1 (1 percent of training data).srt | 12.98 KB | ||
| 11. Building a data augmentation layer to use inside our model.mp4 | 117.46 MB | ||
| 11. Building a data augmentation layer to use inside our model.srt | 16.15 KB | ||
| 12. Visualising what happens when images pass through our data augmentation layer.mp4 | 119.36 MB | ||
| 12. Visualising what happens when images pass through our data augmentation layer.srt | 14.4 KB | ||
| 13. Building Model 1 (with a data augmentation layer and 1% of training data).mp4 | 152.95 MB | ||
| 13. Building Model 1 (with a data augmentation layer and 1% of training data).srt | 22.42 KB | ||
| 14. Building Model 2 (with a data augmentation layer and 10% of training data).mp4 | 159.77 MB | ||
| 14. Building Model 2 (with a data augmentation layer and 10% of training data).srt | 23.45 KB | ||
| 15. Creating a ModelCheckpoint to save our model's weights during training.mp4 | 68.99 MB | ||
| 15. Creating a ModelCheckpoint to save our model's weights during training.srt | 10.72 KB | ||
| 16. Fitting and evaluating Model 2 (and saving its weights using ModelCheckpoint).mp4 | 68.15 MB | ||
| 16. Fitting and evaluating Model 2 (and saving its weights using ModelCheckpoint).srt | 9.85 KB | ||
| 17. Loading and comparing saved weights to our existing trained Model 2.mp4 | 62.67 MB | ||
| 17. Loading and comparing saved weights to our existing trained Model 2.srt | 9.65 KB | ||
| 18. Preparing Model 3 (our first fine-tuned model).mp4 | 198.23 MB | ||
| 18. Preparing Model 3 (our first fine-tuned model).srt | 25.9 KB | ||
| 19. Fitting and evaluating Model 3 (our first fine-tuned model).mp4 | 69.16 MB | ||
| 19. Fitting and evaluating Model 3 (our first fine-tuned model).srt | 10.61 KB | ||
| 2. Importing a script full of helper functions (and saving lots of space).mp4 | 89.39 MB | ||
| 2. Importing a script full of helper functions (and saving lots of space).srt | 9.77 KB | ||
| 20. Comparing our model's results before and after fine-tuning.mp4 | 84.18 MB | ||
| 20. Comparing our model's results before and after fine-tuning.srt | 13.82 KB | ||
| 21. Downloading and preparing data for our biggest experiment yet (Model 4).mp4 | 56.68 MB | ||
| 21. Downloading and preparing data for our biggest experiment yet (Model 4).srt | 8.97 KB | ||
| 22. Preparing our final modelling experiment (Model 4).mp4 | 96.42 MB | ||
| 22. Preparing our final modelling experiment (Model 4).srt | 14.88 KB | ||
| 23. Fine-tuning Model 4 on 100% of the training data and evaluating its results.mp4 | 96.84 MB | ||
| 23. Fine-tuning Model 4 on 100% of the training data and evaluating its results.srt | 14.85 KB | ||
| 24. Comparing our modelling experiment results in TensorBoard.mp4 | 95.75 MB | ||
| 24. Comparing our modelling experiment results in TensorBoard.srt | 15.74 KB | ||
| 25. How to view and delete previous TensorBoard experiments.mp4 | 21.91 MB | ||
| 25. How to view and delete previous TensorBoard experiments.srt | 2.81 KB | ||
| 26. Transfer Learning in TensorFlow Part 2 challenge, exercises and extra-curriculum.html | 2.64 KB | ||
| 3. Downloading and turning our images into a TensorFlow BatchDataset.mp4 | 173.6 MB | ||
| 3. Downloading and turning our images into a TensorFlow BatchDataset.srt | 22.01 KB | ||
| 4. Discussing the four (actually five) modelling experiments we're running.mp4 | 15.87 MB | ||
| 4. Discussing the four (actually five) modelling experiments we're running.srt | 3.58 KB | ||
| 5. Comparing the TensorFlow Keras Sequential API versus the Functional API.mp4 | 26.45 MB | ||
| 5. Comparing the TensorFlow Keras Sequential API versus the Functional API.srt | 4.03 KB | ||
| 6. Creating our first model with the TensorFlow Keras Functional API.mp4 | 132.18 MB | ||
| 6. Creating our first model with the TensorFlow Keras Functional API.srt | 15.84 KB | ||
| 7. Compiling and fitting our first Functional API model.mp4 | 132.84 MB | ||
| 7. Compiling and fitting our first Functional API model.srt | 15.76 KB | ||
| 8. Getting a feature vector from our trained model.mp4 | 147.62 MB | ||
| 8. Getting a feature vector from our trained model.srt | 17.74 KB | ||
| 9. Drilling into the concept of a feature vector (a learned representation).mp4 | 51.5 MB | ||
| 9. Drilling into the concept of a feature vector (a learned representation).srt | 5.39 KB | ||
| 8. Transfer Learning with TensorFlow Part 3 Scaling Up | |||
| 1. Introduction to Transfer Learning Part 3 Scaling Up.mp4 | 41.53 MB | ||
| 1. Introduction to Transfer Learning Part 3 Scaling Up.srt | 10.12 KB | ||
| 10. Downloading a pretrained model to make and evaluate predictions with.mp4 | 78.69 MB | ||
| 10. Downloading a pretrained model to make and evaluate predictions with.srt | 8.91 KB | ||
| 11. Making predictions with our trained model on 25,250 test samples.mp4 | 115.59 MB | ||
| 11. Making predictions with our trained model on 25,250 test samples.srt | 16.24 KB | ||
| 12. Unravelling our test dataset for comparing ground truth labels to predictions.mp4 | 43.81 MB | ||
| 12. Unravelling our test dataset for comparing ground truth labels to predictions.srt | 7.72 KB | ||
| 13. Confirming our model's predictions are in the same order as the test labels.mp4 | 50.54 MB | ||
| 13. Confirming our model's predictions are in the same order as the test labels.srt | 6.77 KB | ||
| 14. Creating a confusion matrix for our model's 101 different classes.mp4 | 156.6 MB | ||
| 14. Creating a confusion matrix for our model's 101 different classes.srt | 17.49 KB | ||
| 15. Evaluating every individual class in our dataset.mp4 | 131.77 MB | ||
| 15. Evaluating every individual class in our dataset.srt | 19.3 KB | ||
| 16. Plotting our model's F1-scores for each separate class.mp4 | 77.94 MB | ||
| 16. Plotting our model's F1-scores for each separate class.srt | 10.69 KB | ||
| 17. Creating a function to load and prepare images for making predictions.mp4 | 109.54 MB | ||
| 17. Creating a function to load and prepare images for making predictions.srt | 15.79 KB | ||
| 18. Making predictions on our test images and evaluating them.mp4 | 171.68 MB | ||
| 18. Making predictions on our test images and evaluating them.srt | 23.48 KB | ||
| 19. Discussing the benefits of finding your model's most wrong predictions.mp4 | 59.3 MB | ||
| 19. Discussing the benefits of finding your model's most wrong predictions.srt | 9.41 KB | ||
| 2. Getting helper functions ready and downloading data to model.mp4 | 131.54 MB | ||
| 2. Getting helper functions ready and downloading data to model.srt | 17.73 KB | ||
| 20. Writing code to uncover our model's most wrong predictions.mp4 | 109.6 MB | ||
| 20. Writing code to uncover our model's most wrong predictions.srt | 17.03 KB | ||
| 21. Plotting and visualising the samples our model got most wrong.mp4 | 125.49 MB | ||
| 21. Plotting and visualising the samples our model got most wrong.srt | 15.45 KB | ||
| 22. Making predictions on and plotting our own custom images.mp4 | 108.3 MB | ||
| 22. Making predictions on and plotting our own custom images.srt | 14.61 KB | ||
| 23. Transfer Learning in TensorFlow Part 3 challenge, exercises and extra-curriculum.html | 2.28 KB | ||
| 3. Outlining the model we're going to build and building a ModelCheckpoint callback.mp4 | 40.61 MB | ||
| 3. Outlining the model we're going to build and building a ModelCheckpoint callback.srt | 7.41 KB | ||
| 4. Creating a data augmentation layer to use with our model.mp4 | 40.56 MB | ||
| 4. Creating a data augmentation layer to use with our model.srt | 6.25 KB | ||
| 5. Creating a headless EfficientNetB0 model with data augmentation built in.mp4 | 80.41 MB | ||
| 5. Creating a headless EfficientNetB0 model with data augmentation built in.srt | 13.45 KB | ||
| 6. Fitting and evaluating our biggest transfer learning model yet.mp4 | 70.15 MB | ||
| 6. Fitting and evaluating our biggest transfer learning model yet.srt | 11.43 KB | ||
| 7. Unfreezing some layers in our base model to prepare for fine-tuning.mp4 | 100.07 MB | ||
| 7. Unfreezing some layers in our base model to prepare for fine-tuning.srt | 16.6 KB | ||
| 8. Fine-tuning our feature extraction model and evaluating its performance.mp4 | 66.23 MB | ||
| 8. Fine-tuning our feature extraction model and evaluating its performance.srt | 11.87 KB | ||
| 9. Saving and loading our trained model.mp4 | 57.41 MB | ||
| 9. Saving and loading our trained model.srt | 8.98 KB | ||
| 9. Milestone Project 1 Food Vision Big™ | |||
| 1. Introduction to Milestone Project 1 Food Vision Big™.mp4 | 42.32 MB | ||
| 1. Introduction to Milestone Project 1 Food Vision Big™.srt | 9.17 KB | ||
| 10. Turning on mixed precision training with TensorFlow.mp4 | 107.71 MB | ||
| 10. Turning on mixed precision training with TensorFlow.srt | 13.89 KB | ||
| 11. Creating a feature extraction model capable of using mixed precision training.mp4 | 107.92 MB | ||
| 11. Creating a feature extraction model capable of using mixed precision training.srt | 17.41 KB | ||
| 12. Checking to see if our model is using mixed precision training layer by layer.mp4 | 87.67 MB | ||
| 12. Checking to see if our model is using mixed precision training layer by layer.srt | 10.27 KB | ||
| 13. Training and evaluating a feature extraction model (Food Vision Big™).mp4 | 89.02 MB | ||
| 13. Training and evaluating a feature extraction model (Food Vision Big™).srt | 14.12 KB | ||
| 14. Introducing your Milestone Project 1 challenge build a model to beat DeepFood.mp4 | 89.12 MB | ||
| 14. Introducing your Milestone Project 1 challenge build a model to beat DeepFood.srt | 11.24 KB | ||
| 15. Milestone Project 1 Food Vision Big™, exercises and extra-curriculum.html | 2.32 KB | ||
| 2. Making sure we have access to the right GPU for mixed precision training.mp4 | 88.15 MB | ||
| 2. Making sure we have access to the right GPU for mixed precision training.srt | 14.06 KB | ||
| 3. Getting helper functions ready.mp4 | 31.09 MB | ||
| 3. Getting helper functions ready.srt | 3.94 KB | ||
| 4. Introduction to TensorFlow Datasets (TFDS).mp4 | 116.84 MB | ||
| 4. Introduction to TensorFlow Datasets (TFDS).srt | 17.62 KB | ||
| 5. Exploring and becoming one with the data (Food101 from TensorFlow Datasets).mp4 | 116.71 MB | ||
| 5. Exploring and becoming one with the data (Food101 from TensorFlow Datasets).srt | 22.34 KB | ||
| 6. Creating a preprocessing function to prepare our data for modelling.mp4 | 132.19 MB | ||
| 6. Creating a preprocessing function to prepare our data for modelling.srt | 18.84 KB | ||
| 7. Batching and preparing our datasets (to make them run fast).mp4 | 132.24 MB | ||
| 7. Batching and preparing our datasets (to make them run fast).srt | 19.22 KB | ||
| 8. Exploring what happens when we batch and prefetch our data.mp4 | 63.82 MB | ||
| 8. Exploring what happens when we batch and prefetch our data.srt | 9.41 KB | ||
| 9. Creating modelling callbacks for our feature extraction model.mp4 | 60.79 MB | ||
| 9. Creating modelling callbacks for our feature extraction model.srt | 9.84 KB | ||
| Download Paid Udemy Courses For Free.url | 116 B | ||
| GetFreeCourses.Co.url | 116 B | ||
| How you can help GetFreeCourses.Co.txt | 182 B | ||
| ▲ 561 total files | |||
TensorFlow Developer Certificate in 2021: Zero to Mastery
Pass the TensorFlow Developer Certification Exam by Google. Become an AI, Machine Learning, and Deep Learning expert!
Udemy Link - https://www.udemy.com/course/tensorflow-developer-certificate-machine-learning-zero-to-mastery/
Please seed as much as you can!
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 30.3 GB | fcs0310 | 3 years | 5 | 3 | |
| 27.6 GB | tutsnode | 5 years | 6 | 9 | |
| 19.5 GB | fcs0310 | 5 years | 0 | 0 | |
| 19.7 GB | tutsnode | 5 years | 6 | 2 | |
|
Coursera - DeepLearning.AI TensorFlow Developer Professional Certificate Posted by
tutsnode in Other
|
1.3 GB | tutsnode | 5 years | 4 | 0 |
All Comments