| 1 - Introduction of Project.mp4 | 8.9 MB | ||
| 10 - Introduction of Project.mp4 | 5.8 MB | ||
| 11 - Setup Environment for ANN.mp4 | 46.6 MB | ||
| 12 - ANN Installation.mp4 | 101.2 MB | ||
| 13 - Import Libraries and Data Preprocessing.mp4 | 36.6 MB | ||
| 14 - Data Preprocessing.mp4 | 76.3 MB | ||
| 15 - Data Preprocessing Continue.mp4 | 85.7 MB | ||
| 16 - Data Exploration.mp4 | 68.4 MB | ||
| 17 - Encoding.mp4 | 50.3 MB | ||
| 18 - Encoding Continue.mp4 | 35.3 MB | ||
| 19 - Preparation of Dataset for Training.mp4 | 26.3 MB | ||
| 2 - Overview of CNN.mp4 | 13.8 MB | ||
| 20 - Steps to Build ANN Part 1.mp4 | 36 MB | ||
| 21 - Steps to Build ANN Part 2.mp4 | 42.8 MB | ||
| 22 - Steps to Build ANN Part 3.mp4 | 22.3 MB | ||
| 23 - Steps to Build ANN Part 4.mp4 | 46.4 MB | ||
| 24 - Predictions.mp4 | 44.3 MB | ||
| 25 - Predictions Continue.mp4 | 40.5 MB | ||
| 26 - Resampling Data with ImbalanceLearn.mp4 | 64.8 MB | ||
| 27 - Resampling Data with ImbalanceLearn Continue.mp4 | 124.9 MB | ||
| 28 - Introduction of Project.mp4 | 14.3 MB | ||
| 29 - Installation.mp4 | 62.3 MB | ||
| 3 - Installations and Dataset Structure.mp4 | 97.1 MB | ||
| 30 - Libraries.mp4 | 99.1 MB | ||
| 31 - Dataset Explore.mp4 | 93.5 MB | ||
| 32 - Import Libraries.mp4 | 20.1 MB | ||
| 33 - Data Preprocessing.mp4 | 48.3 MB | ||
| 34 - Exploratory Data Analysis.mp4 | 47.4 MB | ||
| 35 - Exploratory Data Analysis Continue.mp4 | 53 MB | ||
| 36 - Feature Scaling.mp4 | 60.4 MB | ||
| 37 - Feature Scaling Continue.mp4 | 49.3 MB | ||
| 38 - More on Feature Scaling.mp4 | 29.6 MB | ||
| 39 - Building RNN.mp4 | 43.6 MB | ||
| 4 - Import libraries.mp4 | 25.3 MB | ||
| 40 - Building RNN Continue.mp4 | 26.2 MB | ||
| 41 - Training of Network.mp4 | 53.3 MB | ||
| 42 - Prediction on Test Data.mp4 | 60.7 MB | ||
| 43 - Prediction on Test Data Continue.mp4 | 70.2 MB | ||
| 44 - Final Result Visualization.mp4 | 37.1 MB | ||
| 45 - Introduction to Project.mp4 | 14 MB | ||
| 46 - Google Collab.mp4 | 15.6 MB | ||
| 47 - Importing Packages and Data.mp4 | 22 MB | ||
| 48 - Preprocessing and Model Creation.mp4 | 36.2 MB | ||
| 49 - Training the Model and Prediction.mp4 | 50.1 MB | ||
| 5 - CNN Model and Layers Coding.mp4 | 44.5 MB | ||
| 50 - Model Creation using CNN.mp4 | 88.8 MB | ||
| 51 - CNN Model Prediction.mp4 | 60.7 MB | ||
| 6 - Data Preprocessing and Augmentation.mp4 | 26.2 MB | ||
| 7 - Understanding Data generator.mp4 | 49.1 MB | ||
| 8 - Prediction on Single Image.mp4 | 35.4 MB | ||
| 9 - Understanding Different Models and Accuracy.mp4 | 58.8 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 53 total files | |||
Deep Learning: Neural Networks In Python Using Case Studies
https://DevCourseWeb.com
Published 1/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.41 GB | Duration: 6h 18m
Learn how a neural network is built from basic building blocks using Python
What you'll learn
Learn how a neural network is built from basic building blocks (the neuron)
Learn how Deep Learning works
Code a neural network from scratch in Python and numpy
Describe different types of neural networks and the different types of problems they are used for
Requirements
Basic math (calculus derivatives, matrix arithmetic, probability)
Install Numpy and Python
Don't worry about installing TensorFlow, we will do that in the lectures.
Being familiar with the content of my logistic regression course (cross-entropy cost, gradient descent, neurons, XOR, donut) will give you the proper context for this course
| torrent name | size | uploader | age | seed | leech |
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| 4 GB | freecoursewb | 3 months | 24 | 10 | |
| 582.4 MB | freecoursewb | 6 months | 0 | 0 | |
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Udemy - AWS Networking Deep-Dive Crash Course - Master VPC Essentials Posted by
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