Tensorflow 2.0: Deep Learning and Artificial Intelligence

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Tensorflow 2.0: Deep Learning and Artificial Intelligence

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Tensorflow 2.0: Deep Learning and Artificial Intelligence
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1. Welcome
1. Introduction.mp4
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34.81 MB
1. Introduction.srt
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5.7 KB
2. Outline.mp4
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73.67 MB
2. Outline.srt
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17.1 KB
3. Where to get the code.mp4
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62.91 MB
3. Where to get the code.srt
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15.36 KB
3.1 Colab Notebooks.html
HTML
157 B
3.2 Github Link.html
HTML
120 B
10. GANs (Generative Adversarial Networks)
1. GAN Theory.mp4
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87.16 MB
1. GAN Theory.srt
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20.71 KB
2. GAN Code.mp4
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78.3 MB
2. GAN Code.srt
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14.88 KB
11. Deep Reinforcement Learning (Theory)
1. Deep Reinforcement Learning Section Introduction.mp4
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38.05 MB
1. Deep Reinforcement Learning Section Introduction.srt
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10. Epsilon-Greedy.mp4
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40.11 MB
10. Epsilon-Greedy.srt
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11. Q-Learning.mp4
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61.83 MB
11. Q-Learning.srt
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12. Deep Q-Learning DQN (pt 1).mp4
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56.27 MB
12. Deep Q-Learning DQN (pt 1).srt
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16.43 KB
13. Deep Q-Learning DQN (pt 2).mp4
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49.6 MB
13. Deep Q-Learning DQN (pt 2).srt
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13.21 KB
14. How to Learn Reinforcement Learning.mp4
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37.7 MB
14. How to Learn Reinforcement Learning.srt
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2. Elements of a Reinforcement Learning Problem.mp4
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98.59 MB
2. Elements of a Reinforcement Learning Problem.srt
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3. States, Actions, Rewards, Policies.mp4
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43.33 MB
3. States, Actions, Rewards, Policies.srt
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4. Markov Decision Processes (MDPs).mp4
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49.35 MB
4. Markov Decision Processes (MDPs).srt
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5. The Return.mp4
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21.13 MB
5. The Return.srt
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6. Value Functions and the Bellman Equation.mp4
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43.56 MB
6. Value Functions and the Bellman Equation.srt
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12.51 KB
7. What does it mean to “learn”.mp4
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31.71 MB
7. What does it mean to “learn”.srt
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8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4
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42.74 MB
8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt
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9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4
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52.91 MB
9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt
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14.88 KB
12. Stock Trading Project with Deep Reinforcement Learning
1. Reinforcement Learning Stock Trader Introduction.mp4
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26.04 MB
1. Reinforcement Learning Stock Trader Introduction.srt
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6.84 KB
10. Help! Why is the code slower on my machine.mp4
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42.46 MB
10. Help! Why is the code slower on my machine.srt
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11.72 KB
2. Data and Environment.mp4
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50.97 MB
2. Data and Environment.srt
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15.69 KB
3. Replay Buffer.mp4
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24.04 MB
3. Replay Buffer.srt
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6.94 KB
4. Program Design and Layout.mp4
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25.98 MB
4. Program Design and Layout.srt
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8.64 KB
5. Code pt 1.mp4
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39.55 MB
5. Code pt 1.srt
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7.21 KB
6. Code pt 2.mp4
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68 MB
6. Code pt 2.srt
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7. Code pt 3.mp4
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52.05 MB
7. Code pt 3.srt
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8. Code pt 4.mp4
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52.51 MB
8. Code pt 4.srt
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9. Reinforcement Learning Stock Trader Discussion.mp4
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16.59 MB
9. Reinforcement Learning Stock Trader Discussion.srt
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13. Advanced Tensorflow Usage
1. What is a Web Service (Tensorflow Serving pt 1).mp4
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27.78 MB
1. What is a Web Service (Tensorflow Serving pt 1).srt
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2. Tensorflow Serving pt 2.mp4
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104.99 MB
2. Tensorflow Serving pt 2.srt
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3. Tensorflow Lite (TFLite).mp4
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42.59 MB
3. Tensorflow Lite (TFLite).srt
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11.03 KB
4. Why is Google the King of Distributed Computing.mp4
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44.93 MB
4. Why is Google the King of Distributed Computing.srt
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11.25 KB
5. Training with Distributed Strategies.mp4
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43.54 MB
5. Training with Distributed Strategies.srt
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8.53 KB
6. Using the TPU.mp4
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45.24 MB
6. Using the TPU.srt
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6.96 KB
GetFreeCourses.Co.url
URL
116 B
How you can help GetFreeCourses.Co.txt
TXT
182 B
14. Low-Level Tensorflow
1. Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4
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38.68 MB
1. Differences Between Tensorflow 1.x and Tensorflow 2.x.srt
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2. Constants and Basic Computation.mp4
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40.3 MB
2. Constants and Basic Computation.srt
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3. Variables and Gradient Tape.mp4
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56.05 MB
3. Variables and Gradient Tape.srt
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13.58 KB
4. Build Your Own Custom Model.mp4
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58.55 MB
4. Build Your Own Custom Model.srt
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13.28 KB
15. In-Depth Loss Functions
1. Mean Squared Error.mp4
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33.77 MB
1. Mean Squared Error.srt
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2. Binary Cross Entropy.mp4
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2. Binary Cross Entropy.srt
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3. Categorical Cross Entropy.mp4
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3. Categorical Cross Entropy.srt
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16. In-Depth Gradient Descent
1. Gradient Descent.mp4
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34.92 MB
1. Gradient Descent.srt
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2. Stochastic Gradient Descent.mp4
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22.97 MB
2. Stochastic Gradient Descent.srt
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3. Momentum.mp4
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34.25 MB
3. Momentum.srt
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4. Variable and Adaptive Learning Rates.mp4
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34.85 MB
4. Variable and Adaptive Learning Rates.srt
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5. Adam (pt 1).mp4
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55.12 MB
5. Adam (pt 1).srt
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6. Adam (pt 2).mp4
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52.76 MB
6. Adam (pt 2).srt
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17. Extras
1. How to Choose Hyperparameters.mp4
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37.92 MB
1. How to Choose Hyperparameters.srt
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2. Where Are The Exercises.mp4
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25.98 MB
2. Where Are The Exercises.srt
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5.41 KB
3. Links to TF2.0 Notebooks.html
HTML
8.11 KB
18. Setting up your Environment (FAQ by Student Request)
1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
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150.59 MB
1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt
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14.69 KB
2. Anaconda Environment Setup.mp4
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180.9 MB
2. Anaconda Environment Setup.srt
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19.96 KB
3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4
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167.3 MB
3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.srt
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32.01 KB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)
1. Beginner's Coding Tips.mp4
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75.71 MB
1. Beginner's Coding Tips.srt
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19.02 KB
2. How to Code Yourself (part 1).mp4
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71.85 MB
2. How to Code Yourself (part 1).srt
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22.13 KB
3. How to Code Yourself (part 2).mp4
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49.14 MB
3. How to Code Yourself (part 2).srt
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12.98 KB
4. Proof that using Jupyter Notebook is the same as not using it.mp4
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69.45 MB
4. Proof that using Jupyter Notebook is the same as not using it.srt
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5. Is Theano Dead.mp4
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40.76 MB
5. Is Theano Dead.srt
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GetFreeCourses.Co.url
URL
116 B
2. Google Colab
1. Intro to Google Colab, how to use a GPU or TPU for free.mp4
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53.84 MB
1. Intro to Google Colab, how to use a GPU or TPU for free.srt
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14.13 KB
2. Tensorflow 2.0 in Google Colab.mp4
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40.65 MB
2. Tensorflow 2.0 in Google Colab.srt
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3. Uploading your own data to Google Colab.mp4
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73.59 MB
3. Uploading your own data to Google Colab.srt
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11.98 KB
4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4
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38.93 MB
4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.srt
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5. How to Succeed in this Course.mp4
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43.75 MB
5. How to Succeed in this Course.srt
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8.28 KB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
1. How to Succeed in this Course (Long Version).mp4
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35.22 MB
1. How to Succeed in this Course (Long Version).srt
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14.61 KB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
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105.61 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt
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31.63 KB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
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79.71 MB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt
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16.11 KB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
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108.17 MB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt
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21. Appendix FAQ Finale
1. What is the Appendix.mp4
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16.38 MB
1. What is the Appendix.srt
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2. BONUS Lecture.mp4
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37.79 MB
2. BONUS Lecture.srt
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3. Machine Learning and Neurons
1. What is Machine Learning.mp4
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65.5 MB
1. What is Machine Learning.srt
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18.45 KB
10. Why Keras.mp4
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26.51 MB
10. Why Keras.srt
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11. Suggestion Box.mp4
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27.12 MB
11. Suggestion Box.srt
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2. Code Preparation (Classification Theory).mp4
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59.8 MB
2. Code Preparation (Classification Theory).srt
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20.26 KB
3. Classification Notebook.mp4
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54.54 MB
3. Classification Notebook.srt
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9.4 KB
4. Code Preparation (Regression Theory).mp4
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27.29 MB
4. Code Preparation (Regression Theory).srt
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5. Regression Notebook.mp4
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57.47 MB
5. Regression Notebook.srt
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6. The Neuron.mp4
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42.57 MB
6. The Neuron.srt
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7. How does a model learn.mp4
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47.95 MB
7. How does a model learn.srt
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8. Making Predictions.mp4
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33.88 MB
8. Making Predictions.srt
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9. Saving and Loading a Model.mp4
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29.73 MB
9. Saving and Loading a Model.srt
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4.93 KB
4. Feedforward Artificial Neural Networks
1. Artificial Neural Networks Section Introduction.mp4
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29.82 MB
1. Artificial Neural Networks Section Introduction.srt
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10. ANN for Regression.mp4
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69.27 MB
10. ANN for Regression.srt
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2. Beginners Rejoice The Math in This Course is Optional.mp4
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68.52 MB
2. Beginners Rejoice The Math in This Course is Optional.srt
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3. Forward Propagation.mp4
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46.7 MB
3. Forward Propagation.srt
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4. The Geometrical Picture.mp4
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56.43 MB
4. The Geometrical Picture.srt
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5. Activation Functions.mp4
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80.54 MB
5. Activation Functions.srt
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6. Multiclass Classification.mp4
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41.38 MB
6. Multiclass Classification.srt
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7. How to Represent Images.mp4
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70.46 MB
7. How to Represent Images.srt
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8. Code Preparation (ANN).mp4
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50.92 MB
8. Code Preparation (ANN).srt
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9. ANN for Image Classification.mp4
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47.71 MB
9. ANN for Image Classification.srt
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5. Convolutional Neural Networks
1. What is Convolution (part 1).mp4
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79.77 MB
1. What is Convolution (part 1).srt
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20.16 KB
10. Batch Normalization.mp4
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21.11 MB
10. Batch Normalization.srt
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11. Improving CIFAR-10 Results.mp4
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72.91 MB
11. Improving CIFAR-10 Results.srt
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13.17 KB
2. What is Convolution (part 2).mp4
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22.27 MB
2. What is Convolution (part 2).srt
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3. What is Convolution (part 3).mp4
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27.64 MB
3. What is Convolution (part 3).srt
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4. Convolution on Color Images.mp4
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69.44 MB
4. Convolution on Color Images.srt
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5. CNN Architecture.mp4
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80.58 MB
5. CNN Architecture.srt
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27.89 KB
6. CNN Code Preparation.mp4
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76.88 MB
6. CNN Code Preparation.srt
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7. CNN for Fashion MNIST.mp4
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42.79 MB
7. CNN for Fashion MNIST.srt
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8. CNN for CIFAR-10.mp4
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29.69 MB
8. CNN for CIFAR-10.srt
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9. Data Augmentation.mp4
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34.95 MB
9. Data Augmentation.srt
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GetFreeCourses.Co.url
URL
116 B
How you can help GetFreeCourses.Co.txt
TXT
182 B
6. Recurrent Neural Networks, Time Series, and Sequence Data
1. Sequence Data.mp4
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90.15 MB
1. Sequence Data.srt
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10. GRU and LSTM (pt 2).mp4
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50.36 MB
10. GRU and LSTM (pt 2).srt
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11. A More Challenging Sequence.mp4
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11. A More Challenging Sequence.srt
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12. Demo of the Long Distance Problem.mp4
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124.05 MB
12. Demo of the Long Distance Problem.srt
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13. RNN for Image Classification (Theory).mp4
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29.12 MB
13. RNN for Image Classification (Theory).srt
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14. RNN for Image Classification (Code).mp4
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23.3 MB
14. RNN for Image Classification (Code).srt
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15. Stock Return Predictions using LSTMs (pt 1).mp4
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67.11 MB
15. Stock Return Predictions using LSTMs (pt 1).srt
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16. Stock Return Predictions using LSTMs (pt 2).mp4
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32.97 MB
16. Stock Return Predictions using LSTMs (pt 2).srt
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17. Stock Return Predictions using LSTMs (pt 3).mp4
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67.34 MB
17. Stock Return Predictions using LSTMs (pt 3).srt
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18. Other Ways to Forecast.mp4
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28.33 MB
18. Other Ways to Forecast.srt
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2. Forecasting.mp4
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2. Forecasting.srt
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3. Autoregressive Linear Model for Time Series Prediction.mp4
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71.7 MB
3. Autoregressive Linear Model for Time Series Prediction.srt
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4. Proof that the Linear Model Works.mp4
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16.2 MB
4. Proof that the Linear Model Works.srt
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5. Recurrent Neural Networks.mp4
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83 MB
5. Recurrent Neural Networks.srt
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6. RNN Code Preparation.mp4
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18.43 MB
6. RNN Code Preparation.srt
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7. RNN for Time Series Prediction.mp4
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74.07 MB
7. RNN for Time Series Prediction.srt
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8. Paying Attention to Shapes.mp4
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52.48 MB
8. Paying Attention to Shapes.srt
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9. GRU and LSTM (pt 1).mp4
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79.86 MB
9. GRU and LSTM (pt 1).srt
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7. Natural Language Processing (NLP)
1. Embeddings.mp4
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52.56 MB
1. Embeddings.srt
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2. Code Preparation (NLP).mp4
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57.04 MB
2. Code Preparation (NLP).srt
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3. Text Preprocessing.mp4
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28.76 MB
3. Text Preprocessing.srt
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4. Text Classification with LSTMs.mp4
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50.68 MB
4. Text Classification with LSTMs.srt
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5. CNNs for Text.mp4
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40.4 MB
5. CNNs for Text.srt
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6. Text Classification with CNNs.mp4
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39.62 MB
6. Text Classification with CNNs.srt
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8. Recommender Systems
1. Recommender Systems with Deep Learning Theory.mp4
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68.66 MB
1. Recommender Systems with Deep Learning Theory.srt
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2. Recommender Systems with Deep Learning Code.mp4
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58.81 MB
2. Recommender Systems with Deep Learning Code.srt
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9. Transfer Learning for Computer Vision
1. Transfer Learning Theory.mp4
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55.13 MB
1. Transfer Learning Theory.srt
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10.66 KB
2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4
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31.57 MB
2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).srt
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3. Large Datasets and Data Generators.mp4
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36.56 MB
3. Large Datasets and Data Generators.srt
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4. 2 Approaches to Transfer Learning.mp4
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20.58 MB
4. 2 Approaches to Transfer Learning.srt
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5. Transfer Learning Code (pt 1).mp4
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66.52 MB
5. Transfer Learning Code (pt 1).srt
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6. Transfer Learning Code (pt 2).mp4
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46.05 MB
6. Transfer Learning Code (pt 2).srt
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