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Please note that this page does not hosts or makes available any of the listed filenames. You
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| 001 Anaconda and Jupyter Notebook Install and Setup.en.srt |
22.34KB |
| 001 Anaconda and Jupyter Notebook Install and Setup.mp4 |
98.78MB |
| 001 Convolutional Neural Networks Section Overview.en.srt |
2.69KB |
| 001 Convolutional Neural Networks Section Overview.mp4 |
7.51MB |
| 001 DQN Section Overview.en.srt |
3.10KB |
| 001 DQN Section Overview.mp4 |
10.11MB |
| 001 Introduction to Artificial Neural Networks.en.srt |
3.41KB |
| 001 Introduction to Artificial Neural Networks.mp4 |
9.66MB |
| 001 Introduction to Classical Q-Learning Overview.en.srt |
6.43KB |
| 001 Introduction to Classical Q-Learning Overview.mp4 |
22.61MB |
| 001 Introduction to Matplotlib.en.srt |
6.94KB |
| 001 Introduction to Matplotlib.mp4 |
21.58MB |
| 001 Introduction to Numpy Section.en.srt |
3.12KB |
| 001 Introduction to Numpy Section.mp4 |
11.29MB |
| 001 Introduction to OpenAI Gym Section.en.srt |
1.62KB |
| 001 Introduction to OpenAI Gym Section.mp4 |
6.07MB |
| 001 Overview of Core Concepts for Reinforcement Learning Section.en.srt |
2.77KB |
| 001 Overview of Core Concepts for Reinforcement Learning Section.mp4 |
10.69MB |
| 001 Pandas and Scikit-Learn Overview.html |
1.11KB |
| 001 Welcome Message.html |
2.72KB |
| 001 What is Machine Learning, Deep Learning, and Artificial Intelligence_.en.srt |
17.00KB |
| 001 What is Machine Learning, Deep Learning, and Artificial Intelligence_.mp4 |
54.62MB |
| 002 Agents, Environments, and Policy.en.srt |
18.91KB |
| 002 Agents, Environments, and Policy.mp4 |
62.31MB |
| 002 COURSE_NOTEBOOKS.zip |
55.33MB |
| 002 Course Curriculum Overview.en.srt |
15.82KB |
| 002 Course Curriculum Overview.mp4 |
43.95MB |
| 002 History of DQN.en.srt |
6.92KB |
| 002 History of DQN.mp4 |
28.75MB |
| 002 History of Q-Learning.en.srt |
5.83KB |
| 002 History of Q-Learning.mp4 |
27.07MB |
| 002 Image Filters and Kernels.en.srt |
18.65KB |
| 002 Image Filters and Kernels.mp4 |
72.33MB |
| 002 Matplotlib Basics.en.srt |
20.39KB |
| 002 Matplotlib Basics.mp4 |
53.61MB |
| 002 Note on Environment Setup.html |
1.59KB |
| 002 NumPy Arrays.en.srt |
33.09KB |
| 002 NumPy Arrays.mp4 |
109.65MB |
| 002 OpenAI Overview and History.en.srt |
17.81KB |
| 002 OpenAI Overview and History.mp4 |
69.73MB |
| 002 Pandas - Series Part One.en.srt |
13.88KB |
| 002 Pandas - Series Part One.mp4 |
38.65MB |
| 002 Perceptron Model.en.srt |
15.97KB |
| 002 Perceptron Model.mp4 |
48.01MB |
| 002 Supervised Machine Learning Process.en.srt |
20.44KB |
| 002 Supervised Machine Learning Process.mp4 |
71.69MB |
| 003 Convolutional Layers.en.srt |
22.05KB |
| 003 Convolutional Layers.mp4 |
57.98MB |
| 003 Course Success and Overview.en.srt |
11.97KB |
| 003 Course Success and Overview.mp4 |
42.06MB |
| 003 DQN Theory and Intuition - Part One - Review of Core RL Ideas.en.srt |
7.37KB |
| 003 DQN Theory and Intuition - Part One - Review of Core RL Ideas.mp4 |
23.94MB |
| 003 Environment Setup Walkthrough.en.srt |
17.36KB |
| 003 Environment Setup Walkthrough.mp4 |
71.19MB |
| 003 Matplotlib - Understanding the Figure Object.en.srt |
11.96KB |
| 003 Matplotlib - Understanding the Figure Object.mp4 |
25.81MB |
| 003 Neural Networks.en.srt |
11.58KB |
| 003 Neural Networks.mp4 |
35.91MB |
| 003 Numpy Operations - Part One.en.srt |
16.85KB |
| 003 Numpy Operations - Part One.mp4 |
46.36MB |
| 003 OpenAI Gym - Documentation Tour.en.srt |
23.19KB |
| 003 OpenAI Gym - Documentation Tour.mp4 |
146.53MB |
| 003 Pandas - Series Part Two.en.srt |
15.96KB |
| 003 Pandas - Series Part Two.mp4 |
45.49MB |
| 003 Q-Learning Theory - Part One - Table Intuition.en.srt |
23.41KB |
| 003 Q-Learning Theory - Part One - Table Intuition.mp4 |
77.51MB |
| 003 Rewards, Discount Factors, and Bellman Equation.en.srt |
20.31KB |
| 003 Rewards, Discount Factors, and Bellman Equation.mp4 |
56.74MB |
| 004 Activation Functions.en.srt |
17.42KB |
| 004 Activation Functions.mp4 |
62.52MB |
| 004 COURSE_NOTEBOOKS.zip |
55.33MB |
| 004 Deterministic vs. Stochastic Processes.en.srt |
8.05KB |
| 004 Deterministic vs. Stochastic Processes.mp4 |
27.29MB |
| 004 DQN Theory and Intuition - Part Two - Neural Networks for RL.en.srt |
17.09KB |
| 004 DQN Theory and Intuition - Part Two - Neural Networks for RL.mp4 |
46.52MB |
| 004 Matplotlib - Implementing Figures and Axes.en.srt |
21.79KB |
| 004 Matplotlib - Implementing Figures and Axes.mp4 |
59.05MB |
| 004 Numpy Operations - Part Two.en.srt |
12.51KB |
| 004 Numpy Operations - Part Two.mp4 |
48.64MB |
| 004 OpenAI Gym - Environment Key Ideas.en.srt |
13.53KB |
| 004 OpenAI Gym - Environment Key Ideas.mp4 |
37.28MB |
| 004 Pandas - DataFrames - Part One.en.srt |
30.10KB |
| 004 Pandas - DataFrames - Part One.mp4 |
114.40MB |
| 004 Pooling Layers.en.srt |
10.99KB |
| 004 Pooling Layers.mp4 |
27.64MB |
| 004 Q-Learning Theory - Part Two - Q Target Equation.en.srt |
16.79KB |
| 004 Q-Learning Theory - Part Two - Q Target Equation.mp4 |
54.29MB |
| 005 DQN Theory and Intuition - Part Three - Feedback and Function Approximation.en.srt |
31.44KB |
| 005 DQN Theory and Intuition - Part Three - Feedback and Function Approximation.mp4 |
88.34MB |
| 005 Matplotlib - Figure Parameters.en.srt |
7.95KB |
| 005 Matplotlib - Figure Parameters.mp4 |
23.77MB |
| 005 MNIST Data Set Overview.en.srt |
7.65KB |
| 005 MNIST Data Set Overview.mp4 |
24.75MB |
| 005 Multi-Class Classification Considerations.en.srt |
16.84KB |
| 005 Multi-Class Classification Considerations.mp4 |
46.07MB |
| 005 Numpy Exercise Overview.en.srt |
2.15KB |
| 005 Numpy Exercise Overview.mp4 |
11.54MB |
| 005 OpenAI Gym - Working with the Environment.en.srt |
43.45KB |
| 005 OpenAI Gym - Working with the Environment.mp4 |
137.50MB |
| 005 Pandas - DataFrames - Part Two.en.srt |
13.77KB |
| 005 Pandas - DataFrames - Part Two.mp4 |
54.04MB |
| 005 Q-Learning Theory - Part Three - Q-Update Equation.en.srt |
11.66KB |
| 005 Q-Learning Theory - Part Three - Q-Update Equation.mp4 |
37.52MB |
| 005 Tabular Reinforcement Learning.html |
1.08KB |
| 006 CNN on MNIST - The Data.en.srt |
19.42KB |
| 006 CNN on MNIST - The Data.mp4 |
59.81MB |
| 006 Cost Functions and Gradient Descent.en.srt |
28.73KB |
| 006 Cost Functions and Gradient Descent.mp4 |
76.00MB |
| 006 DQN Theory and Intuition - Part Four - Experience Replay.en.srt |
29.82KB |
| 006 DQN Theory and Intuition - Part Four - Experience Replay.mp4 |
96.01MB |
| 006 Matplotlib - Subplots Functionality.en.srt |
29.70KB |
| 006 Matplotlib - Subplots Functionality.mp4 |
96.22MB |
| 006 Numpy Exercise Solutions.en.srt |
11.29KB |
| 006 Numpy Exercise Solutions.mp4 |
48.57MB |
| 006 OpenAI Gym - Agent Interacting with the Environment.en.srt |
32.03KB |
| 006 OpenAI Gym - Agent Interacting with the Environment.mp4 |
116.41MB |
| 006 Pandas - DataFrames - Part Three.en.srt |
21.39KB |
| 006 Pandas - DataFrames - Part Three.mp4 |
89.52MB |
| 006 Q-Learning Theory - Part Four - Programmatic Q Updates.en.srt |
15.36KB |
| 006 Q-Learning Theory - Part Four - Programmatic Q Updates.mp4 |
58.17MB |
| 007 Backpropagation.en.srt |
21.84KB |
| 007 Backpropagation.mp4 |
57.95MB |
| 007 CNN on MNIST - Creating and Training the Model.en.srt |
26.01KB |
| 007 CNN on MNIST - Creating and Training the Model.mp4 |
98.89MB |
| 007 DQN Theory and Intuition - Part Five - Mapping Key Ideas to Code.en.srt |
24.04KB |
| 007 DQN Theory and Intuition - Part Five - Mapping Key Ideas to Code.mp4 |
81.49MB |
| 007 Matplotlib Styling - Legends.en.srt |
10.73KB |
| 007 Matplotlib Styling - Legends.mp4 |
34.09MB |
| 007 Pandas - DataFrames - Part Four.en.srt |
21.89KB |
| 007 Pandas - DataFrames - Part Four.mp4 |
96.75MB |
| 007 Q-Learning Implementation - Part One - Environment Setup.en.srt |
24.10KB |
| 007 Q-Learning Implementation - Part One - Environment Setup.mp4 |
88.24MB |
| 008 CNN on MNIST - Model Evaluation.en.srt |
10.10KB |
| 008 CNN on MNIST - Model Evaluation.mp4 |
38.47MB |
| 008 DQN Manual Implementation - Part One - Imports and Environment.en.srt |
7.85KB |
| 008 DQN Manual Implementation - Part One - Imports and Environment.mp4 |
20.81MB |
| 008 Matplotlib Styling - Colors and Styles.en.srt |
21.85KB |
| 008 Matplotlib Styling - Colors and Styles.mp4 |
81.17MB |
| 008 Q-Learning Implementation - Part Two - Table and Hyperparameters.en.srt |
17.27KB |
| 008 Q-Learning Implementation - Part Two - Table and Hyperparameters.mp4 |
43.07MB |
| 008 Scikit-Learn - Using Train-Test-Split.en.srt |
18.11KB |
| 008 Scikit-Learn - Using Train-Test-Split.mp4 |
60.47MB |
| 008 TensorFlow vs. Keras Explained.en.srt |
3.15KB |
| 008 TensorFlow vs. Keras Explained.mp4 |
10.44MB |
| 009 Advanced Matplotlib Commands (Optional).en.srt |
6.74KB |
| 009 Advanced Matplotlib Commands (Optional).mp4 |
40.47MB |
| 009 CNN on CIFAR-10 - The Data.en.srt |
18.12KB |
| 009 CNN on CIFAR-10 - The Data.mp4 |
64.30MB |
| 009 DQN Manual Implementation - Part Two - Artificial Neural Network.en.srt |
11.51KB |
| 009 DQN Manual Implementation - Part Two - Artificial Neural Network.mp4 |
31.92MB |
| 009 Keras Syntax - Preparing the Data.en.srt |
16.18KB |
| 009 Keras Syntax - Preparing the Data.mp4 |
50.31MB |
| 009 Q-Learning Implementation - Part Three - Update Functions.en.srt |
25.55KB |
| 009 Q-Learning Implementation - Part Three - Update Functions.mp4 |
92.93MB |
| 009 Scikit-Learn - Using Metrics.en.srt |
22.46KB |
| 009 Scikit-Learn - Using Metrics.mp4 |
77.29MB |
| 010 CNN on CIFAR-10 - Evaluating the Model.en.srt |
11.31KB |
| 010 CNN on CIFAR-10 - Evaluating the Model.mp4 |
45.35MB |
| 010 DQN Manual Implementation - Part Three - Hyperparameters and Functions.en.srt |
27.80KB |
| 010 DQN Manual Implementation - Part Three - Hyperparameters and Functions.mp4 |
84.74MB |
| 010 Keras Syntax - Creating and Training the Model.en.srt |
21.45KB |
| 010 Keras Syntax - Creating and Training the Model.mp4 |
84.34MB |
| 010 Matplotlib Exercise Questions Overview.en.srt |
9.68KB |
| 010 Matplotlib Exercise Questions Overview.mp4 |
50.74MB |
| 010 Q-Learning Implementation - Part Four - Agent Training.en.srt |
26.76KB |
| 010 Q-Learning Implementation - Part Four - Agent Training.mp4 |
107.01MB |
| 011 Downloading Data Set for Real Image Lectures.en.srt |
9.05KB |
| 011 Downloading Data Set for Real Image Lectures.mp4 |
28.13MB |
| 011 DQN Manual Implementation - Part Four - Model Training.en.srt |
25.66KB |
| 011 DQN Manual Implementation - Part Four - Model Training.mp4 |
106.91MB |
| 011 Keras Syntax - Model Evaluation.en.srt |
18.58KB |
| 011 Keras Syntax - Model Evaluation.mp4 |
64.78MB |
| 011 Matplotlib Exercise Questions - Solutions.en.srt |
25.55KB |
| 011 Matplotlib Exercise Questions - Solutions.mp4 |
123.16MB |
| 011 Q-Learning Implementation - Part Five - Visualization and Utilization.en.srt |
15.99KB |
| 011 Q-Learning Implementation - Part Five - Visualization and Utilization.mp4 |
56.57MB |
| 012 CNN on Real Image Files - Reading in the Data.en.srt |
21.73KB |
| 012 CNN on Real Image Files - Reading in the Data.mp4 |
80.39MB |
| 012 Continuous Q-Learning Theory - Part One - Environment Setup.en.srt |
20.96KB |
| 012 Continuous Q-Learning Theory - Part One - Environment Setup.mp4 |
54.42MB |
| 012 DQN - Keras-RL2 - Part One - Overview.en.srt |
11.76KB |
| 012 DQN - Keras-RL2 - Part One - Overview.mp4 |
53.70MB |
| 012 Keras Regression - Exploratory Data Analysis.en.srt |
27.98KB |
| 012 Keras Regression - Exploratory Data Analysis.mp4 |
136.97MB |
| 013 CNN on Real Image Files - Data Generation.en.srt |
24.33KB |
| 013 CNN on Real Image Files - Data Generation.mp4 |
87.73MB |
| 013 Continuous Q-Learning Theory - Part Two- Q-Table Shape.en.srt |
25.54KB |
| 013 Continuous Q-Learning Theory - Part Two- Q-Table Shape.mp4 |
85.71MB |
| 013 DQN - Keras-RL2 - Part Two - Imports and Environment.en.srt |
5.00KB |
| 013 DQN - Keras-RL2 - Part Two - Imports and Environment.mp4 |
13.96MB |
| 013 Keras Regression - EDA Continued.en.srt |
19.91KB |
| 013 Keras Regression - EDA Continued.mp4 |
76.26MB |
| 014 CNN on Real Image Files - Creating the Model.en.srt |
21.21KB |
| 014 CNN on Real Image Files - Creating the Model.mp4 |
90.48MB |
| 014 Continuous Q-Learning Theory - Part Three - Discretization Theory.en.srt |
7.82KB |
| 014 Continuous Q-Learning Theory - Part Three - Discretization Theory.mp4 |
24.71MB |
| 014 DQN - Keras-RL2 - Part Three - Creating the ANN.en.srt |
9.01KB |
| 014 DQN - Keras-RL2 - Part Three - Creating the ANN.mp4 |
25.99MB |
| 014 Keras Regression - Data Preprocessing and Model Creation.en.srt |
12.73KB |
| 014 Keras Regression - Data Preprocessing and Model Creation.mp4 |
46.98MB |
| 015 CNN on Real Image Files - Model Evaluation.en.srt |
12.92KB |
| 015 CNN on Real Image Files - Model Evaluation.mp4 |
46.96MB |
| 015 Continuous Q-Learning - Part Four - Discretization Implementation.en.srt |
27.03KB |
| 015 Continuous Q-Learning - Part Four - Discretization Implementation.mp4 |
86.19MB |
| 015 DQN - Keras-RL2 - Part Four - DQN Agent.en.srt |
23.13KB |
| 015 DQN - Keras-RL2 - Part Four - DQN Agent.mp4 |
84.12MB |
| 015 Keras Regression - Model Evaluation and Predictions.en.srt |
16.94KB |
| 015 Keras Regression - Model Evaluation and Predictions.mp4 |
68.93MB |
| 016 CNN Exercise Project Overview.en.srt |
3.99KB |
| 016 CNN Exercise Project Overview.mp4 |
17.81MB |
| 016 Continuous Q-Learning - Part Five - Functions and Hyperparameters.en.srt |
16.33KB |
| 016 Continuous Q-Learning - Part Five - Functions and Hyperparameters.mp4 |
45.35MB |
| 016 DQN - Exercise Overview.en.srt |
5.89KB |
| 016 DQN - Exercise Overview.mp4 |
28.34MB |
| 016 Keras Classification - EDA and Preprocessing.en.srt |
12.24KB |
| 016 Keras Classification - EDA and Preprocessing.mp4 |
56.19MB |
| 017 CNN Exercise Project Solutions.en.srt |
12.77KB |
| 017 CNN Exercise Project Solutions.mp4 |
55.88MB |
| 017 Continuous Q-Learning - Part Six - Training and Usage.en.srt |
31.74KB |
| 017 Continuous Q-Learning - Part Six - Training and Usage.mp4 |
108.80MB |
| 017 DQN - Exercise Solutions.en.srt |
15.45KB |
| 017 DQN - Exercise Solutions.mp4 |
62.54MB |
| 017 Keras Classification - Overfitting and Evaluation.en.srt |
25.32KB |
| 017 Keras Classification - Overfitting and Evaluation.mp4 |
111.19MB |
| 018 Keras Classification - Overview of Project Options.en.srt |
2.61KB |
| 018 Keras Classification - Overview of Project Options.mp4 |
7.86MB |
| 018 Q-Learning Exercise Project.en.srt |
12.45KB |
| 018 Q-Learning Exercise Project.mp4 |
66.26MB |
| 019 Keras Project Notebook Exercise Overview.en.srt |
13.11KB |
| 019 Keras Project Notebook Exercise Overview.mp4 |
80.57MB |
| 019 Q-Learning Exercise Project - Solutions.en.srt |
33.51KB |
| 019 Q-Learning Exercise Project - Solutions.mp4 |
177.07MB |
| 020 Keras Project Solution - Exploratoy Data Analysis.en.srt |
30.04KB |
| 020 Keras Project Solution - Exploratoy Data Analysis.mp4 |
143.67MB |
| 021 Keras Project Solutions - Missing Data - Part One.en.srt |
21.81KB |
| 021 Keras Project Solutions - Missing Data - Part One.mp4 |
96.76MB |
| 022 Keras Project Solutions - Dealing with Missing Data - Part Two.en.srt |
18.89KB |
| 022 Keras Project Solutions - Dealing with Missing Data - Part Two.mp4 |
85.41MB |
| 023 Keras Project Solutions - Categorical Data.en.srt |
27.17KB |
| 023 Keras Project Solutions - Categorical Data.mp4 |
125.03MB |
| 024 Keras Project Solutions - Data Preprocessing.en.srt |
5.45KB |
| 024 Keras Project Solutions - Data Preprocessing.mp4 |
23.97MB |
| 025 Keras Project Solutions- Creating and Training the Model.en.srt |
6.09KB |
| 025 Keras Project Solutions- Creating and Training the Model.mp4 |
29.76MB |
| 026 Keras Project Solutions - Model Evaluation.en.srt |
14.75KB |
| 026 Keras Project Solutions - Model Evaluation.mp4 |
63.17MB |
| 027 Tensorboard.en.srt |
30.65KB |
| 027 Tensorboard.mp4 |
144.23MB |
| 033 Advertising.csv |
4.11KB |
| 110 DQNNaturePaper.pdf |
4.39MB |
| external-assets-links.txt |
180B |