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Deep Learning - Artificial Neural Networks with Tensorflow

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File Name
Size
Chapter 3 Feedforward Artificial Neural Networks/004. Activation Functions.mp4
62 MB
Chapter 1 Welcome/001. Introduction.mp4
19 MB
Chapter 1 Welcome/002. Outline.en.srt
7.5 kB
Chapter 1 Welcome/002. Outline.mp4
22 MB
Chapter 2 Machine Learning and Neurons/001. What Is Machine Learning.en.srt
20 kB
Chapter 2 Machine Learning and Neurons/001. What Is Machine Learning.mp4
54 MB
Chapter 2 Machine Learning and Neurons/002. Code Preparation (Classification Theory).en.srt
22 kB
Chapter 2 Machine Learning and Neurons/002. Code Preparation (Classification Theory).mp4
48 MB
Chapter 2 Machine Learning and Neurons/003. Classification Notebook.en.srt
10 kB
Chapter 2 Machine Learning and Neurons/003. Classification Notebook.mp4
45 MB
Chapter 2 Machine Learning and Neurons/004. Code Preparation (Regression Theory).en.srt
9.6 kB
Chapter 2 Machine Learning and Neurons/004. Code Preparation (Regression Theory).mp4
24 MB
Chapter 2 Machine Learning and Neurons/005. Regression Notebook.en.srt
13 kB
Chapter 2 Machine Learning and Neurons/005. Regression Notebook.mp4
48 MB
Chapter 2 Machine Learning and Neurons/006. The Neuron.en.srt
14 kB
Chapter 2 Machine Learning and Neurons/006. The Neuron.mp4
34 MB
Chapter 2 Machine Learning and Neurons/007. How Does a Model Learn .en.srt
15 kB
Chapter 2 Machine Learning and Neurons/007. How Does a Model Learn .mp4
39 MB
Chapter 2 Machine Learning and Neurons/008. Making Predictions.en.srt
8.8 kB
Chapter 2 Machine Learning and Neurons/008. Making Predictions.mp4
30 MB
Chapter 2 Machine Learning and Neurons/009. Saving and Loading a Model.en.srt
5.5 kB
Chapter 2 Machine Learning and Neurons/009. Saving and Loading a Model.mp4
28 MB
Chapter 2 Machine Learning and Neurons/010. Why Keras.en.srt
6.5 kB
Chapter 2 Machine Learning and Neurons/010. Why Keras.mp4
18 MB
Chapter 2 Machine Learning and Neurons/011. Suggestion Box.en.srt
4.6 kB
Chapter 2 Machine Learning and Neurons/011. Suggestion Box.mp4
17 MB
Chapter 3 Feedforward Artificial Neural Networks/001. Artificial Neural Networks Section Introduction.en.srt
8.5 kB
Chapter 3 Feedforward Artificial Neural Networks/001. Artificial Neural Networks Section Introduction.mp4
27 MB
Chapter 3 Feedforward Artificial Neural Networks/002. Forward Propagation.en.srt
13 kB
Chapter 3 Feedforward Artificial Neural Networks/002. Forward Propagation.mp4
34 MB
Chapter 3 Feedforward Artificial Neural Networks/003. The Geometrical Picture.en.srt
13 kB
Chapter 3 Feedforward Artificial Neural Networks/003. The Geometrical Picture.mp4
39 MB
Chapter 3 Feedforward Artificial Neural Networks/004. Activation Functions.en.srt
24 kB
Chapter 1 Welcome/001. Introduction.en.srt
3.5 kB
Chapter 3 Feedforward Artificial Neural Networks/005. Multiclass Classification.en.srt
12 kB
Chapter 3 Feedforward Artificial Neural Networks/005. Multiclass Classification.mp4
34 MB
Chapter 3 Feedforward Artificial Neural Networks/006. How to Represent Images.en.srt
17 kB
Chapter 3 Feedforward Artificial Neural Networks/006. How to Represent Images.mp4
50 MB
Chapter 3 Feedforward Artificial Neural Networks/007. Code Preparation (Artificial Neural Networks).en.srt
17 kB
Chapter 3 Feedforward Artificial Neural Networks/007. Code Preparation (Artificial Neural Networks).mp4
42 MB
Chapter 3 Feedforward Artificial Neural Networks/008. ANN for Image Classification.en.srt
11 kB
Chapter 3 Feedforward Artificial Neural Networks/008. ANN for Image Classification.mp4
40 MB
Chapter 3 Feedforward Artificial Neural Networks/009. ANN for Regression.en.srt
14 kB
Chapter 3 Feedforward Artificial Neural Networks/009. ANN for Regression.mp4
56 MB
Chapter 3 Feedforward Artificial Neural Networks/010. How to Choose Hyperparameters.en.srt
8.6 kB
Chapter 3 Feedforward Artificial Neural Networks/010. How to Choose Hyperparameters.mp4
24 MB
Chapter 4 In-Depth Loss Functions/001. Mean Squared Error.en.srt
12 kB
Chapter 4 In-Depth Loss Functions/001. Mean Squared Error.mp4
30 MB
Chapter 4 In-Depth Loss Functions/002. Binary Cross Entropy.en.srt
7.6 kB
Chapter 4 In-Depth Loss Functions/002. Binary Cross Entropy.mp4
20 MB
Chapter 4 In-Depth Loss Functions/003. Categorical Cross Entropy.en.srt
10 kB
Chapter 4 In-Depth Loss Functions/003. Categorical Cross Entropy.mp4
27 MB
Chapter 5 In-Depth Gradient Descent/001. Gradient Descent.en.srt
10 kB
Chapter 5 In-Depth Gradient Descent/001. Gradient Descent.mp4
28 MB
Chapter 5 In-Depth Gradient Descent/002. Stochastic Gradient Descent.en.srt
5.6 kB
Chapter 5 In-Depth Gradient Descent/002. Stochastic Gradient Descent.mp4
21 MB
Chapter 5 In-Depth Gradient Descent/003. Momentum.en.srt
8.0 kB
Chapter 5 In-Depth Gradient Descent/003. Momentum.mp4
29 MB
Chapter 5 In-Depth Gradient Descent/004. Variable and Adaptive Learning Rates.en.srt
16 kB
Chapter 5 In-Depth Gradient Descent/004. Variable and Adaptive Learning Rates.mp4
33 MB
Chapter 5 In-Depth Gradient Descent/005. Adam Optimization (Part 1).en.srt
18 kB
Chapter 5 In-Depth Gradient Descent/005. Adam Optimization (Part 1).mp4
42 MB
Chapter 5 In-Depth Gradient Descent/006. Adam Optimization (Part 2).en.srt
15 kB
Chapter 5 In-Depth Gradient Descent/006. Adam Optimization (Part 2).mp4
40 MB