Udemy - MQL4 Special Course - Two Pairs Arbitrage 2022

Files:

• Get Bonus Downloads Here.url (0.2 KB)
~Get Your Files Here ! 1 - Introduction
• 1. Introduction.en_US.srt (7.4 KB)
• 1. Introduction.mp4 (22.3 MB)
• 2. Reinforcement Learning series.html (6.9 KB)
• 3. Google Colab.en_US.srt (1.7 KB)
• 3. Google Colab.mp4 (3.6 MB)
• 4. Where to begin.en_US.srt (1.2 KB)
• 4. Where to begin.mp4 (2.1 MB)
• 5. Complete code.html (5.4 KB)
• 6. Connect with me on social media.html (5.7 KB)
__MACOSX advanced_rl_pg_methods_complete
• _2_REINFORCE_continuous.ipynb (0.3 KB)
• _4_proximal_policy_optimization.ipynb (0.3 KB)
• _5_generalized_advantage_estimation.ipynb (0.3 KB)
• _6_TRPO.ipynb (0.3 KB)
advanced_rl_pg_methods_complete
• 1_REINFORCE.ipynb (15.5 KB)
• 2_REINFORCE_continuous.ipynb (20.9 KB)
• 3_advantage_actor_critic.ipynb (14.8 KB)
• 4_proximal_policy_optimization.ipynb (20.3 KB)
• 5_generalized_advantage_estimation.ipynb (21.2 KB)
• 6_TRPO.ipynb (29.0 KB)
10 - Advantage Actor Critic (A2C)
• 59. A2C.en_US.srt (10.6 KB)
• 59. A2C.mp4 (29.2 MB)
• 60. Link to the code notebook.html (5.6 KB)
• 61. Create the policy and value network.en_US.srt (4.5 KB)
• 61. Create the policy and value network.mp4 (27.0 MB)
• 62. Create the environment.en_US.srt (5.9 KB)
• 62. Create the environment.mp4 (17.4 MB)
• 63. Create the dataset.en_US.srt (2.5 KB)
• 63. Create the dataset.mp4 (10.0 MB)
• 64. Implement A2C - Part 1.en_US.srt (4.9 KB)
• 64. Implement A2C - Part 1.mp4 (19.1 MB)
• 65. Implement A2C - Part 2.en_US.srt (8.9 KB)
• 65. Implement A2C - Part 2.mp4 (51.5 MB)
• 66. Check the resulting agent.en_US.srt (2.3 KB)
• 66. Check the resulting agent.mp4 (19.2 MB)
11 - Trust region methods
• 67. Line search vs trust region methods.en_US.srt (2.6 KB)
• 67. Line search vs trust region methods.mp4 (4.2 MB)
• 68. Line search methods.en_US.srt (7.2 KB)
• 68. Line search methods.mp4 (20.5 MB)
• 69. Trust region methods 1.en_US.srt (3.4 KB)
• 69. Trust region methods 1.mp4 (8.9 MB)
• 70. Kullback-Leibler divergence.en_US.srt (4.7 KB)
• 70. Kullback-Leibler divergence.mp4 (8.2 MB)
• 71. Trust region methods 2.en_US.srt (11.4 KB)
• 71. Trust region methods 2.mp4 (20.3 MB)
• 72. Trust region methods 3.en_US.srt (3.1 KB)
• 72. Trust region methods 3.mp4 (4.9 MB)
12 - Proximal Policy Optimization (PPO)
• 73. Proximal Policy Optimization.en_US.srt (9.9 KB)
• 73. Proximal Policy Optimization.mp4 (20.8 MB)
• 74. Link to the code notebook.html (5.6 KB)
• 75. Create the environment.en_US.srt (7.8 KB)
• 75. Create the environment.mp4 (61.2 MB)
• 76. Create the dataset.en_US.srt (6.7 KB)
• 76. Create the dataset.mp4 (26.4 MB)
• 77. Create the PPO algorithm - Part 1.en_US.srt (4.9 KB)
• 77. Create the PPO algorithm - Part 1.mp4 (29.2 MB)
• 78. Create the PPO algorithm - Part 2.en_US.srt (10.2 KB)
• 78. Create the PPO algorithm - Part 2.mp4 (91.6 MB)
• 79. Check the resulting agent.en_US.srt (1.9 KB)
• 79. Check the resulting agent.mp4 (13.2 MB)
13 - Generalized Advantage Estimation (GAE)
• 80. Generalized Advantage Estimation.en_US.srt (12.5 KB)
• 80. Generalized Advantage Estimation.mp4 (21.2 MB)
• 81. Link to the code notebook.html (5.6 KB)
• 82. Create the Half Cheetah environment.en_US.srt (5.0 KB)
• 82. Create the Half Cheetah environment.mp4 (38.7 MB)
• 83. Create the dataset.en_US.srt (10.0 KB)
• 83. Create the dataset.mp4 (40.1 MB)
• 84. PPO with generalized advantage estimation - Part 1.en_US.srt (3.3 KB)
• 84. PPO with generalized advantage estimation - Part 1.mp4 (15.3 MB)
• 85. PPO with generalized advantage estimation - Part 2.en_US.srt (5.2 KB)
• 85. PPO with generalized advantage estimation - Part 2.mp4 (33.8 MB)
• 86. Checking the resulting agent.en_US.srt (1.0 KB)
• 86. Checking the resulting agent.mp4 (10.4 MB)
14 - Trust Region Policy Optimization (TRPO)
• 87. Trust region policy optimization 1.en_US.srt (3.9 KB)
• 87. Trust region policy optimization 1.mp4 (6.5 MB)
• 88. Trust region policy optimization 2.en_US.srt (6.2 KB)
• 88. Trust region policy optimization 2.mp4 (11.1 MB)
• 89. Link to the code notebook.html (5.6 KB)
• 90. TRPO in code - Part 1.en_US.srt (3.5 KB)
• 90. TRPO in code - Part 1.mp4 (19.0 MB)
• 91. TRPO in code - Part 2.en_US.srt (2.5 KB)
• 91. TRPO in code - Part 2.mp4 (11.0 MB)
• 92. TRPO in code - Part 3.en_US.srt (2.1 KB)
• 92. TRPO in code - Part 3.mp4 (6.8 MB)
• 93. TRPO in code - Part 4.en_US.srt (4.7 KB)
• 93. TRPO in code - Part 4.mp4 (19.7 MB)
• 94. TRPO in code - Part 5.en_US.srt (8.9 KB)
• 94. TRPO in code - Part 5.mp4 (43.1 MB)
• 95. TRPO in code - Part 6.en_US.srt (0.9 KB)
• 95. TRPO in code - Part 6.mp4 (6.7 MB)
15 - Final steps
• 96. Final steps.html (6.0 KB)
• 97. Connect with me on social media.html (5.7 KB)
2 - Refresher The Markov Decision Process (MDP)
• 10. Trajectory vs episode.en_US.srt (1.1 KB)
• 10. Trajectory vs episode.mp4 (3.0 MB)
• 11. Reward vs Return.en_US.srt (1.6 KB)
• 11. Reward vs Return.mp4 (3.2 MB)
• 12. Discount factor.en_US.srt (4.1 KB)
• 12. Discount factor.mp4 (8.8 MB)
• 13. Policy.en_US.srt (2.1 KB)
• 13. Policy.mp4 (4.5 MB)
• 14. State values v(s) and action values q(s,a).en_US.srt (1.2 KB)