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[Udemy] Practical AI with Python and Reinforcement Learning (07.2021)
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[Udemy] Practical AI with Python and Reinforcement Learning (07.2021)
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文件列表
11 Classical Q Learning/019 Q-Learning Exercise Project - Solutions.mp4
185.7 MB
10 Open AI Gym Overview/003 OpenAI Gym - Documentation Tour.mp4
153.7 MB
07 Artificial Neural Network and TensorFlow Basics/027 Tensorboard.mp4
151.2 MB
07 Artificial Neural Network and TensorFlow Basics/020 Keras Project Solution - Exploratoy Data Analysis.mp4
150.6 MB
10 Open AI Gym Overview/005 OpenAI Gym - Working with the Environment.mp4
144.2 MB
07 Artificial Neural Network and TensorFlow Basics/012 Keras Regression - Exploratory Data Analysis.mp4
143.6 MB
07 Artificial Neural Network and TensorFlow Basics/023 Keras Project Solutions - Categorical Data.mp4
131.1 MB
04 Matplotlib and Visualization Overview/011 Matplotlib Exercise Questions - Solutions.mp4
129.1 MB
10 Open AI Gym Overview/006 OpenAI Gym - Agent Interacting with the Environment.mp4
122.1 MB
06 Pandas and Scikit-Learn Crash Course/004 Pandas - DataFrames - Part One.mp4
120.0 MB
07 Artificial Neural Network and TensorFlow Basics/017 Keras Classification - Overfitting and Evaluation.mp4
116.6 MB
03 Numpy Basics Overview/002 NumPy Arrays.mp4
115.0 MB
11 Classical Q Learning/017 Continuous Q-Learning - Part Six - Training and Usage.mp4
114.1 MB
11 Classical Q Learning/010 Q-Learning Implementation - Part Four - Agent Training.mp4
112.2 MB
12 Deep Q-Learning/011 DQN Manual Implementation - Part Four - Model Training.mp4
112.1 MB
08 Convolutional Neural Networks with TensorFlow/007 CNN on MNIST - Creating and Training the Model.mp4
103.7 MB
02 Course Set-Up and Installation Procedures/001 Anaconda and Jupyter Notebook Install and Setup.mp4
103.6 MB
07 Artificial Neural Network and TensorFlow Basics/021 Keras Project Solutions - Missing Data - Part One.mp4
101.5 MB
06 Pandas and Scikit-Learn Crash Course/007 Pandas - DataFrames - Part Four.mp4
101.4 MB
04 Matplotlib and Visualization Overview/006 Matplotlib - Subplots Functionality.mp4
100.9 MB
12 Deep Q-Learning/006 DQN Theory and Intuition - Part Four - Experience Replay.mp4
100.7 MB
11 Classical Q Learning/009 Q-Learning Implementation - Part Three - Update Functions.mp4
97.4 MB
08 Convolutional Neural Networks with TensorFlow/014 CNN on Real Image Files - Creating the Model.mp4
94.9 MB
06 Pandas and Scikit-Learn Crash Course/006 Pandas - DataFrames - Part Three.mp4
93.9 MB
12 Deep Q-Learning/005 DQN Theory and Intuition - Part Three - Feedback and Function Approximation.mp4
92.6 MB
11 Classical Q Learning/007 Q-Learning Implementation - Part One - Environment Setup.mp4
92.5 MB
08 Convolutional Neural Networks with TensorFlow/013 CNN on Real Image Files - Data Generation.mp4
92.0 MB
11 Classical Q Learning/015 Continuous Q-Learning - Part Four - Discretization Implementation.mp4
90.4 MB
11 Classical Q Learning/013 Continuous Q-Learning Theory - Part Two- Q-Table Shape.mp4
89.9 MB
07 Artificial Neural Network and TensorFlow Basics/022 Keras Project Solutions - Dealing with Missing Data - Part Two.mp4
89.6 MB
12 Deep Q-Learning/010 DQN Manual Implementation - Part Three - Hyperparameters and Functions.mp4
88.9 MB
07 Artificial Neural Network and TensorFlow Basics/010 Keras Syntax - Creating and Training the Model.mp4
88.4 MB
12 Deep Q-Learning/015 DQN - Keras-RL2 - Part Four - DQN Agent.mp4
88.2 MB
12 Deep Q-Learning/007 DQN Theory and Intuition - Part Five - Mapping Key Ideas to Code.mp4
85.5 MB
04 Matplotlib and Visualization Overview/008 Matplotlib Styling - Colors and Styles.mp4
85.1 MB
07 Artificial Neural Network and TensorFlow Basics/019 Keras Project Notebook Exercise Overview.mp4
84.5 MB
08 Convolutional Neural Networks with TensorFlow/012 CNN on Real Image Files - Reading in the Data.mp4
84.3 MB
11 Classical Q Learning/003 Q-Learning Theory - Part One - Table Intuition.mp4
81.3 MB
06 Pandas and Scikit-Learn Crash Course/009 Scikit-Learn - Using Metrics.mp4
81.0 MB
07 Artificial Neural Network and TensorFlow Basics/013 Keras Regression - EDA Continued.mp4
80.0 MB
07 Artificial Neural Network and TensorFlow Basics/006 Cost Functions and Gradient Descent.mp4
79.7 MB
08 Convolutional Neural Networks with TensorFlow/002 Image Filters and Kernels.mp4
75.8 MB
05 Machine Learning, Deep Learning, and Reinforcement Learning/002 Supervised Machine Learning Process.mp4
75.2 MB
02 Course Set-Up and Installation Procedures/003 Environment Setup Walkthrough.mp4
74.7 MB
10 Open AI Gym Overview/002 OpenAI Overview and History.mp4
73.1 MB
07 Artificial Neural Network and TensorFlow Basics/015 Keras Regression - Model Evaluation and Predictions.mp4
72.3 MB
11 Classical Q Learning/018 Q-Learning Exercise Project.mp4
69.5 MB
07 Artificial Neural Network and TensorFlow Basics/011 Keras Syntax - Model Evaluation.mp4
67.9 MB
08 Convolutional Neural Networks with TensorFlow/009 CNN on CIFAR-10 - The Data.mp4
67.4 MB
07 Artificial Neural Network and TensorFlow Basics/026 Keras Project Solutions - Model Evaluation.mp4
66.2 MB
12 Deep Q-Learning/017 DQN - Exercise Solutions.mp4
65.6 MB
07 Artificial Neural Network and TensorFlow Basics/004 Activation Functions.mp4
65.6 MB
09 Reinforcement Learning - Core Concepts/002 Agents, Environments, and Policy.mp4
65.3 MB
06 Pandas and Scikit-Learn Crash Course/008 Scikit-Learn - Using Train-Test-Split.mp4
63.4 MB
08 Convolutional Neural Networks with TensorFlow/006 CNN on MNIST - The Data.mp4
62.7 MB
04 Matplotlib and Visualization Overview/004 Matplotlib - Implementing Figures and Axes.mp4
61.9 MB
11 Classical Q Learning/006 Q-Learning Theory - Part Four - Programmatic Q Updates.mp4
61.0 MB
08 Convolutional Neural Networks with TensorFlow/003 Convolutional Layers.mp4
60.8 MB
07 Artificial Neural Network and TensorFlow Basics/007 Backpropagation.mp4
60.8 MB
09 Reinforcement Learning - Core Concepts/003 Rewards, Discount Factors, and Bellman Equation.mp4
59.5 MB
11 Classical Q Learning/011 Q-Learning Implementation - Part Five - Visualization and Utilization.mp4
59.3 MB
07 Artificial Neural Network and TensorFlow Basics/016 Keras Classification - EDA and Preprocessing.mp4
58.9 MB
08 Convolutional Neural Networks with TensorFlow/017 CNN Exercise Project Solutions.mp4
58.6 MB
01 Course Overview/002 COURSE_NOTEBOOKS.zip
58.0 MB
02 Course Set-Up and Installation Procedures/004 COURSE_NOTEBOOKS.zip
58.0 MB
05 Machine Learning, Deep Learning, and Reinforcement Learning/001 What is Machine Learning, Deep Learning, and Artificial Intelligence_.mp4
57.3 MB
11 Classical Q Learning/012 Continuous Q-Learning Theory - Part One - Environment Setup.mp4
57.1 MB
11 Classical Q Learning/004 Q-Learning Theory - Part Two - Q Target Equation.mp4
56.9 MB
06 Pandas and Scikit-Learn Crash Course/005 Pandas - DataFrames - Part Two.mp4
56.7 MB
12 Deep Q-Learning/012 DQN - Keras-RL2 - Part One - Overview.mp4
56.3 MB
04 Matplotlib and Visualization Overview/002 Matplotlib Basics.mp4
56.2 MB
04 Matplotlib and Visualization Overview/010 Matplotlib Exercise Questions Overview.mp4
53.2 MB
07 Artificial Neural Network and TensorFlow Basics/009 Keras Syntax - Preparing the Data.mp4
52.8 MB
03 Numpy Basics Overview/004 Numpy Operations - Part Two.mp4
51.0 MB
03 Numpy Basics Overview/006 Numpy Exercise Solutions.mp4
50.9 MB
07 Artificial Neural Network and TensorFlow Basics/002 Perceptron Model.mp4
50.3 MB
07 Artificial Neural Network and TensorFlow Basics/014 Keras Regression - Data Preprocessing and Model Creation.mp4
49.3 MB
08 Convolutional Neural Networks with TensorFlow/015 CNN on Real Image Files - Model Evaluation.mp4
49.2 MB
12 Deep Q-Learning/004 DQN Theory and Intuition - Part Two - Neural Networks for RL.mp4
48.8 MB
03 Numpy Basics Overview/003 Numpy Operations - Part One.mp4
48.6 MB
07 Artificial Neural Network and TensorFlow Basics/005 Multi-Class Classification Considerations.mp4
48.3 MB
06 Pandas and Scikit-Learn Crash Course/003 Pandas - Series Part Two.mp4
47.7 MB
11 Classical Q Learning/016 Continuous Q-Learning - Part Five - Functions and Hyperparameters.mp4
47.6 MB
08 Convolutional Neural Networks with TensorFlow/010 CNN on CIFAR-10 - Evaluating the Model.mp4
47.6 MB
01 Course Overview/002 Course Curriculum Overview.mp4
46.1 MB
11 Classical Q Learning/008 Q-Learning Implementation - Part Two - Table and Hyperparameters.mp4
45.2 MB
01 Course Overview/003 Course Success and Overview.mp4
44.1 MB
04 Matplotlib and Visualization Overview/009 Advanced Matplotlib Commands (Optional).mp4
42.4 MB
06 Pandas and Scikit-Learn Crash Course/002 Pandas - Series Part One.mp4
40.5 MB
08 Convolutional Neural Networks with TensorFlow/008 CNN on MNIST - Model Evaluation.mp4
40.3 MB
11 Classical Q Learning/005 Q-Learning Theory - Part Three - Q-Update Equation.mp4
39.3 MB
10 Open AI Gym Overview/004 OpenAI Gym - Environment Key Ideas.mp4
39.1 MB
07 Artificial Neural Network and TensorFlow Basics/003 Neural Networks.mp4
37.7 MB
04 Matplotlib and Visualization Overview/007 Matplotlib Styling - Legends.mp4
35.7 MB
12 Deep Q-Learning/009 DQN Manual Implementation - Part Two - Artificial Neural Network.mp4
33.5 MB
07 Artificial Neural Network and TensorFlow Basics/025 Keras Project Solutions- Creating and Training the Model.mp4
31.2 MB
12 Deep Q-Learning/002 History of DQN.mp4
30.1 MB
12 Deep Q-Learning/016 DQN - Exercise Overview.mp4
29.7 MB
08 Convolutional Neural Networks with TensorFlow/011 Downloading Data Set for Real Image Lectures.mp4
29.5 MB
08 Convolutional Neural Networks with TensorFlow/004 Pooling Layers.mp4
29.0 MB
09 Reinforcement Learning - Core Concepts/004 Deterministic vs. Stochastic Processes.mp4
28.6 MB
11 Classical Q Learning/002 History of Q-Learning.mp4
28.4 MB
12 Deep Q-Learning/014 DQN - Keras-RL2 - Part Three - Creating the ANN.mp4
27.3 MB
04 Matplotlib and Visualization Overview/003 Matplotlib - Understanding the Figure Object.mp4
27.1 MB
08 Convolutional Neural Networks with TensorFlow/005 MNIST Data Set Overview.mp4
25.9 MB
11 Classical Q Learning/014 Continuous Q-Learning Theory - Part Three - Discretization Theory.mp4
25.9 MB
07 Artificial Neural Network and TensorFlow Basics/024 Keras Project Solutions - Data Preprocessing.mp4
25.1 MB
12 Deep Q-Learning/003 DQN Theory and Intuition - Part One - Review of Core RL Ideas.mp4
25.1 MB
04 Matplotlib and Visualization Overview/005 Matplotlib - Figure Parameters.mp4
24.9 MB
11 Classical Q Learning/001 Introduction to Classical Q-Learning Overview.mp4
23.7 MB
04 Matplotlib and Visualization Overview/001 Introduction to Matplotlib.mp4
22.6 MB
12 Deep Q-Learning/008 DQN Manual Implementation - Part One - Imports and Environment.mp4
21.8 MB
08 Convolutional Neural Networks with TensorFlow/016 CNN Exercise Project Overview.mp4
18.7 MB
12 Deep Q-Learning/013 DQN - Keras-RL2 - Part Two - Imports and Environment.mp4
14.6 MB
03 Numpy Basics Overview/005 Numpy Exercise Overview.mp4
12.1 MB
03 Numpy Basics Overview/001 Introduction to Numpy Section.mp4
11.8 MB
09 Reinforcement Learning - Core Concepts/001 Overview of Core Concepts for Reinforcement Learning Section.mp4
11.2 MB
07 Artificial Neural Network and TensorFlow Basics/008 TensorFlow vs. Keras Explained.mp4
10.9 MB
12 Deep Q-Learning/001 DQN Section Overview.mp4
10.6 MB
07 Artificial Neural Network and TensorFlow Basics/001 Introduction to Artificial Neural Networks.mp4
10.1 MB
07 Artificial Neural Network and TensorFlow Basics/018 Keras Classification - Overview of Project Options.mp4
8.2 MB
08 Convolutional Neural Networks with TensorFlow/001 Convolutional Neural Networks Section Overview.mp4
7.9 MB
10 Open AI Gym Overview/001 Introduction to OpenAI Gym Section.mp4
6.4 MB
12 Deep Q-Learning/110 DQNNaturePaper.pdf
4.6 MB
10 Open AI Gym Overview/005 OpenAI Gym - Working with the Environment.en.srt
44.5 kB
11 Classical Q Learning/019 Q-Learning Exercise Project - Solutions.en.srt
34.3 kB
03 Numpy Basics Overview/002 NumPy Arrays.en.srt
33.9 kB
10 Open AI Gym Overview/006 OpenAI Gym - Agent Interacting with the Environment.en.srt
32.8 kB
11 Classical Q Learning/017 Continuous Q-Learning - Part Six - Training and Usage.en.srt
32.5 kB
12 Deep Q-Learning/005 DQN Theory and Intuition - Part Three - Feedback and Function Approximation.en.srt
32.2 kB
07 Artificial Neural Network and TensorFlow Basics/027 Tensorboard.en.srt
31.4 kB
06 Pandas and Scikit-Learn Crash Course/004 Pandas - DataFrames - Part One.en.srt
30.8 kB
07 Artificial Neural Network and TensorFlow Basics/020 Keras Project Solution - Exploratoy Data Analysis.en.srt
30.8 kB
12 Deep Q-Learning/006 DQN Theory and Intuition - Part Four - Experience Replay.en.srt
30.5 kB
04 Matplotlib and Visualization Overview/006 Matplotlib - Subplots Functionality.en.srt
30.4 kB
07 Artificial Neural Network and TensorFlow Basics/006 Cost Functions and Gradient Descent.en.srt
29.4 kB
07 Artificial Neural Network and TensorFlow Basics/012 Keras Regression - Exploratory Data Analysis.en.srt
28.7 kB
12 Deep Q-Learning/010 DQN Manual Implementation - Part Three - Hyperparameters and Functions.en.srt
28.5 kB
07 Artificial Neural Network and TensorFlow Basics/023 Keras Project Solutions - Categorical Data.en.srt
27.8 kB
11 Classical Q Learning/015 Continuous Q-Learning - Part Four - Discretization Implementation.en.srt
27.7 kB
11 Classical Q Learning/010 Q-Learning Implementation - Part Four - Agent Training.en.srt
27.4 kB
08 Convolutional Neural Networks with TensorFlow/007 CNN on MNIST - Creating and Training the Model.en.srt
26.6 kB
12 Deep Q-Learning/011 DQN Manual Implementation - Part Four - Model Training.en.srt
26.3 kB
04 Matplotlib and Visualization Overview/011 Matplotlib Exercise Questions - Solutions.en.srt
26.2 kB
11 Classical Q Learning/009 Q-Learning Implementation - Part Three - Update Functions.en.srt
26.2 kB
11 Classical Q Learning/013 Continuous Q-Learning Theory - Part Two- Q-Table Shape.en.srt
26.2 kB
07 Artificial Neural Network and TensorFlow Basics/017 Keras Classification - Overfitting and Evaluation.en.srt
25.9 kB
08 Convolutional Neural Networks with TensorFlow/013 CNN on Real Image Files - Data Generation.en.srt
24.9 kB
11 Classical Q Learning/007 Q-Learning Implementation - Part One - Environment Setup.en.srt
24.7 kB
12 Deep Q-Learning/007 DQN Theory and Intuition - Part Five - Mapping Key Ideas to Code.en.srt
24.6 kB
11 Classical Q Learning/003 Q-Learning Theory - Part One - Table Intuition.en.srt
24.0 kB
10 Open AI Gym Overview/003 OpenAI Gym - Documentation Tour.en.srt
23.7 kB
12 Deep Q-Learning/015 DQN - Keras-RL2 - Part Four - DQN Agent.en.srt
23.7 kB
06 Pandas and Scikit-Learn Crash Course/009 Scikit-Learn - Using Metrics.en.srt
23.0 kB
02 Course Set-Up and Installation Procedures/001 Anaconda and Jupyter Notebook Install and Setup.en.srt
22.9 kB
08 Convolutional Neural Networks with TensorFlow/003 Convolutional Layers.en.srt
22.6 kB
06 Pandas and Scikit-Learn Crash Course/007 Pandas - DataFrames - Part Four.en.srt
22.4 kB
04 Matplotlib and Visualization Overview/008 Matplotlib Styling - Colors and Styles.en.srt
22.4 kB
07 Artificial Neural Network and TensorFlow Basics/007 Backpropagation.en.srt
22.4 kB
07 Artificial Neural Network and TensorFlow Basics/021 Keras Project Solutions - Missing Data - Part One.en.srt
22.3 kB
04 Matplotlib and Visualization Overview/004 Matplotlib - Implementing Figures and Axes.en.srt
22.3 kB
08 Convolutional Neural Networks with TensorFlow/012 CNN on Real Image Files - Reading in the Data.en.srt
22.2 kB
07 Artificial Neural Network and TensorFlow Basics/010 Keras Syntax - Creating and Training the Model.en.srt
22.0 kB
06 Pandas and Scikit-Learn Crash Course/006 Pandas - DataFrames - Part Three.en.srt
21.9 kB
08 Convolutional Neural Networks with TensorFlow/014 CNN on Real Image Files - Creating the Model.en.srt
21.7 kB
11 Classical Q Learning/012 Continuous Q-Learning Theory - Part One - Environment Setup.en.srt
21.5 kB
05 Machine Learning, Deep Learning, and Reinforcement Learning/002 Supervised Machine Learning Process.en.srt
20.9 kB
04 Matplotlib and Visualization Overview/002 Matplotlib Basics.en.srt
20.9 kB
09 Reinforcement Learning - Core Concepts/003 Rewards, Discount Factors, and Bellman Equation.en.srt
20.8 kB
07 Artificial Neural Network and TensorFlow Basics/013 Keras Regression - EDA Continued.en.srt
20.4 kB
08 Convolutional Neural Networks with TensorFlow/006 CNN on MNIST - The Data.en.srt
19.9 kB
09 Reinforcement Learning - Core Concepts/002 Agents, Environments, and Policy.en.srt
19.4 kB
07 Artificial Neural Network and TensorFlow Basics/022 Keras Project Solutions - Dealing with Missing Data - Part Two.en.srt
19.3 kB
08 Convolutional Neural Networks with TensorFlow/002 Image Filters and Kernels.en.srt
19.1 kB
07 Artificial Neural Network and TensorFlow Basics/011 Keras Syntax - Model Evaluation.en.srt
19.0 kB
08 Convolutional Neural Networks with TensorFlow/009 CNN on CIFAR-10 - The Data.en.srt
18.6 kB
06 Pandas and Scikit-Learn Crash Course/008 Scikit-Learn - Using Train-Test-Split.en.srt
18.5 kB
10 Open AI Gym Overview/002 OpenAI Overview and History.en.srt
18.2 kB
07 Artificial Neural Network and TensorFlow Basics/004 Activation Functions.en.srt
17.8 kB
02 Course Set-Up and Installation Procedures/003 Environment Setup Walkthrough.en.srt
17.8 kB
11 Classical Q Learning/008 Q-Learning Implementation - Part Two - Table and Hyperparameters.en.srt
17.7 kB
12 Deep Q-Learning/004 DQN Theory and Intuition - Part Two - Neural Networks for RL.en.srt
17.5 kB
05 Machine Learning, Deep Learning, and Reinforcement Learning/001 What is Machine Learning, Deep Learning, and Artificial Intelligence_.en.srt
17.4 kB
07 Artificial Neural Network and TensorFlow Basics/015 Keras Regression - Model Evaluation and Predictions.en.srt
17.3 kB
03 Numpy Basics Overview/003 Numpy Operations - Part One.en.srt
17.3 kB
07 Artificial Neural Network and TensorFlow Basics/005 Multi-Class Classification Considerations.en.srt
17.2 kB
11 Classical Q Learning/004 Q-Learning Theory - Part Two - Q Target Equation.en.srt
17.2 kB
11 Classical Q Learning/016 Continuous Q-Learning - Part Five - Functions and Hyperparameters.en.srt
16.7 kB
07 Artificial Neural Network and TensorFlow Basics/009 Keras Syntax - Preparing the Data.en.srt
16.6 kB
11 Classical Q Learning/011 Q-Learning Implementation - Part Five - Visualization and Utilization.en.srt
16.4 kB
07 Artificial Neural Network and TensorFlow Basics/002 Perceptron Model.en.srt
16.4 kB
06 Pandas and Scikit-Learn Crash Course/003 Pandas - Series Part Two.en.srt
16.3 kB
01 Course Overview/002 Course Curriculum Overview.en.srt
16.2 kB
12 Deep Q-Learning/017 DQN - Exercise Solutions.en.srt
15.8 kB
11 Classical Q Learning/006 Q-Learning Theory - Part Four - Programmatic Q Updates.en.srt
15.7 kB
07 Artificial Neural Network and TensorFlow Basics/026 Keras Project Solutions - Model Evaluation.en.srt
15.1 kB
06 Pandas and Scikit-Learn Crash Course/002 Pandas - Series Part One.en.srt
14.2 kB
06 Pandas and Scikit-Learn Crash Course/005 Pandas - DataFrames - Part Two.en.srt
14.1 kB
10 Open AI Gym Overview/004 OpenAI Gym - Environment Key Ideas.en.srt
13.9 kB
07 Artificial Neural Network and TensorFlow Basics/019 Keras Project Notebook Exercise Overview.en.srt
13.4 kB
08 Convolutional Neural Networks with TensorFlow/015 CNN on Real Image Files - Model Evaluation.en.srt
13.2 kB
08 Convolutional Neural Networks with TensorFlow/017 CNN Exercise Project Solutions.en.srt
13.1 kB
07 Artificial Neural Network and TensorFlow Basics/014 Keras Regression - Data Preprocessing and Model Creation.en.srt
13.0 kB
03 Numpy Basics Overview/004 Numpy Operations - Part Two.en.srt
12.8 kB
11 Classical Q Learning/018 Q-Learning Exercise Project.en.srt
12.7 kB
07 Artificial Neural Network and TensorFlow Basics/016 Keras Classification - EDA and Preprocessing.en.srt
12.5 kB
01 Course Overview/003 Course Success and Overview.en.srt
12.3 kB
04 Matplotlib and Visualization Overview/003 Matplotlib - Understanding the Figure Object.en.srt
12.2 kB
12 Deep Q-Learning/012 DQN - Keras-RL2 - Part One - Overview.en.srt
12.0 kB
11 Classical Q Learning/005 Q-Learning Theory - Part Three - Q-Update Equation.en.srt
11.9 kB
07 Artificial Neural Network and TensorFlow Basics/003 Neural Networks.en.srt
11.9 kB
12 Deep Q-Learning/009 DQN Manual Implementation - Part Two - Artificial Neural Network.en.srt
11.8 kB
08 Convolutional Neural Networks with TensorFlow/010 CNN on CIFAR-10 - Evaluating the Model.en.srt
11.6 kB
03 Numpy Basics Overview/006 Numpy Exercise Solutions.en.srt
11.6 kB
08 Convolutional Neural Networks with TensorFlow/004 Pooling Layers.en.srt
11.3 kB
04 Matplotlib and Visualization Overview/007 Matplotlib Styling - Legends.en.srt
11.0 kB
08 Convolutional Neural Networks with TensorFlow/008 CNN on MNIST - Model Evaluation.en.srt
10.3 kB
04 Matplotlib and Visualization Overview/010 Matplotlib Exercise Questions Overview.en.srt
9.9 kB
08 Convolutional Neural Networks with TensorFlow/011 Downloading Data Set for Real Image Lectures.en.srt
9.3 kB
12 Deep Q-Learning/014 DQN - Keras-RL2 - Part Three - Creating the ANN.en.srt
9.2 kB
09 Reinforcement Learning - Core Concepts/004 Deterministic vs. Stochastic Processes.en.srt
8.2 kB
04 Matplotlib and Visualization Overview/005 Matplotlib - Figure Parameters.en.srt
8.1 kB
12 Deep Q-Learning/008 DQN Manual Implementation - Part One - Imports and Environment.en.srt
8.0 kB
11 Classical Q Learning/014 Continuous Q-Learning Theory - Part Three - Discretization Theory.en.srt
8.0 kB
08 Convolutional Neural Networks with TensorFlow/005 MNIST Data Set Overview.en.srt
7.8 kB
12 Deep Q-Learning/003 DQN Theory and Intuition - Part One - Review of Core RL Ideas.en.srt
7.5 kB
04 Matplotlib and Visualization Overview/001 Introduction to Matplotlib.en.srt
7.1 kB
12 Deep Q-Learning/002 History of DQN.en.srt
7.1 kB
04 Matplotlib and Visualization Overview/009 Advanced Matplotlib Commands (Optional).en.srt
6.9 kB
11 Classical Q Learning/001 Introduction to Classical Q-Learning Overview.en.srt
6.6 kB
07 Artificial Neural Network and TensorFlow Basics/025 Keras Project Solutions- Creating and Training the Model.en.srt
6.2 kB
12 Deep Q-Learning/016 DQN - Exercise Overview.en.srt
6.0 kB
11 Classical Q Learning/002 History of Q-Learning.en.srt
6.0 kB
07 Artificial Neural Network and TensorFlow Basics/024 Keras Project Solutions - Data Preprocessing.en.srt
5.6 kB
12 Deep Q-Learning/013 DQN - Keras-RL2 - Part Two - Imports and Environment.en.srt
5.1 kB
06 Pandas and Scikit-Learn Crash Course/033 Advertising.csv
4.2 kB
08 Convolutional Neural Networks with TensorFlow/016 CNN Exercise Project Overview.en.srt
4.1 kB
07 Artificial Neural Network and TensorFlow Basics/001 Introduction to Artificial Neural Networks.en.srt
3.5 kB
07 Artificial Neural Network and TensorFlow Basics/008 TensorFlow vs. Keras Explained.en.srt
3.2 kB
03 Numpy Basics Overview/001 Introduction to Numpy Section.en.srt
3.2 kB
12 Deep Q-Learning/001 DQN Section Overview.en.srt
3.2 kB
09 Reinforcement Learning - Core Concepts/001 Overview of Core Concepts for Reinforcement Learning Section.en.srt
2.8 kB
01 Course Overview/001 Welcome Message.html
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08 Convolutional Neural Networks with TensorFlow/001 Convolutional Neural Networks Section Overview.en.srt
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07 Artificial Neural Network and TensorFlow Basics/018 Keras Classification - Overview of Project Options.en.srt
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03 Numpy Basics Overview/005 Numpy Exercise Overview.en.srt
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10 Open AI Gym Overview/001 Introduction to OpenAI Gym Section.en.srt
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02 Course Set-Up and Installation Procedures/002 Note on Environment Setup.html
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06 Pandas and Scikit-Learn Crash Course/001 Pandas and Scikit-Learn Overview.html
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09 Reinforcement Learning - Core Concepts/005 Tabular Reinforcement Learning.html
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08 Convolutional Neural Networks with TensorFlow/external-assets-links.txt
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