Advanced AI Deep Reinforcement Learning in Python, name of the training video series in the field of data and analyze it, and in the branches, programming language, Python can be. This course is specifically on teaching advanced artificial intelligence focuses. You to help of the programming language Python, and familiarity with the science of deep learning to dominate significantly, you want to hit. Course, you as a comprehensive course for deep learning as well as neural networks are expected to be. This course as a period of the efficient skills you to dramatically upgrade will give.
Familiarity with calculus and probability. object-oriented programming, etc. programming, Python, etc. programming, Numpy, linear regression, and other items to you in understanding the content of this course is a great help will. This course is also for professionals and students, has a track record of strong technical wanting to learn techniques, advanced artificial intelligence and design is published. At the end of this course you, the students cherish, to people fluent in the use of a variety of neural networks and deep in different levels, you will.
Cases in which the course is taught:
- Familiarity with the various factors, including the DQN and A3C in deep learning
- Learn a variety of algorithms, deep learning, advanced in solving the problems
- Understanding and learning the Q-Learning, to help learning, advanced neural networks
- Learn how to use neural networks Convolutional with Q-Learning, Deep
- Learning and understanding with networks, RBF
Profile course the Advanced AI Deep Reinforcement Learning in Python
- Language : English
- Duration Time : 10h 35m
- Number of courses: 79
- Instructor : Lazy Programmer, Inc.
- File format : mp4
This course the Advanced AI Deep Reinforcement Learning in Python
Prerequisite course Advanced AI Deep Reinforcement Learning in Python
- Know reinforcement learning basics, MDPs, Dynamic Programming, Monte Carlo, TD Learning
- Calculus and probability
- Experience building machine learning models in Python and Numpy
- Know how to build a feedforward, convolutional and recurrent neural network using Theano and Tensorflow
After the Extract with the Player your custom view.
Version 2019/12 compared to 2018/12 at least 4 minutes increased. About 600 MB also increase the volume of have been.
Version 2020/4 compared to 2019/12 no change in the number of courses and total time, and time headings is not. Changes in content are not specified.
Version 2020/7 compared to 2020/4 number of 6 lessons and 1.5 hours increase.
Version 2020/12 compared to 2020/7 about 7 minutes, increase the time.
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