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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-reinforcement-learning-deep-q-learning-and-trfl/
课程评论：没有评论
课程名称：Python强化学习、深度Q学习与TRFL 课程概述：强化学习（RL）使您能够在商业环境中开发智能、快速且自学习的系统。这是一种有效的方法，可以训练学习代理，解决各种人工智能问题，包括游戏、自驾车和机器人，以及从数据中心节能到智能仓储解决方案的企业应用。本课程覆盖了通过将深度神经网络架构与强化学习结合起来，在深度强化学习领域取得的重大进展与成功。您将了解强化学习的概念、优势以及其日益受欢迎的原因。课程内容还包括马尔可夫决策过程（MDP）、蒙特卡洛树搜索、动态规划（如政策迭代和价值迭代）、时间差学习（如Q学习和SARSA）。您将学习使用TensorFlow和Keras构建卷积神经网络模型，并了解在游戏环境中运用人工智能的方法，通过OpenAI Gym进行实操。到课程结束时，您将探索强化学习，并通过实际数据和人工智能（AI）获得实践经验，以构建智能系统。 讲师介绍： - Lauren Washington：目前担任smartQED的首席数据科学家和机器学习开发者，曾在Topix担任数据科学家，在谷歌担任支付风险策略师，并在尼尔森担任统计分析师。她对机器学习教学充满热情，并为数据科学社区提供指导与回馈。 - Kaiser Hamid Rabbi：数据科学家，对人工智能、机器学习和数据科学充满热情，专注于大数据科学技术，努力理解项目经验背后的领域知识。 - Colibri Digital：一家成立于2015年的技术咨询公司，致力于帮助客户应对不断变化的技术世界，拥有在大数据、数据科学和云计算领域的深厚专业知识。 - Jim DiLorenzo：自由程序员和强化学习爱好者，毕业于哥伦比亚大学，目前攻读计算机科学硕士学位，积极进行强化学习实验。 通过该课程，您将获得关于强化学习的深入理解，并能够应用所学知识与技能，建立智能系统以应对现实世界中的复杂挑战。
Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of problems in Artificial Intelligence-from games, self-driving cars and robots to enterprise applications that range from data centre energy saving (cooling data centres) to smart warehousing solutions.This course covers the major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. You will be introduced to the concept of Reinforcement Learning, its advantages and why it's gaining so much popularity. This course also discusses on Markov Decision Process (MDPs), Monte Carlo tree searches, dynamic programmings such as policy and value iteration, temporal difference learning such as Q-learning and SARSA. You will learn to build convolutional neural network models using TensorFlow and Keras. You will also learn the use of artificial intelligence in a gaming environment with the help of OpenAI Gym.By the end of this course, you will explore reinforcement learning and will have hands-on experience with real data and artificial intelligence (AI) to build intelligent systems.Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:● Lauren Washington is currently the Lead Data Scientist and Machine Learning Developer for smartQED, an AI driven start-up. Lauren worked as a Data Scientist for Topix, Payments Risk Strategist for Google (Google Wallet/Android Pay), Statistical Analyst for Nielsen, and Big Data Intern for the National Opinion Research Center through the University of Chicago. Lauren is also passionate about teaching Machine Learning. She's currently giving back to the data science community as a Thinkful Data Science Bootcamp Mentor and a Packt Publishing technical video reviewer. She also earned a Data Science certificate from General Assembly San Francisco (2016), a MA in the Quantitative Methods in the Social Sciences (Applied Statistical Methods) from Columbia University (2012), and a BA in Economics from Spelman College (2010). Lauren is a leader in AI, in Silicon Valley, with a passion for knowledge gathering and sharing.● Kaiser Hamid Rabbi is a Data Scientist who is super-passionate about Artificial Intelligence, Machine Learning, and Data Science. He has entirely devoted himself to learning more about Big Data Science technologies such as Python, Machine Learning, Deep Learning, Artificial Intelligence, Reinforcement Learning, Data Mining, Data Analysis, Recommender Systems and so on over the last 4 years. Kaiser also has a huge interest in Lygometry (things we know we do not know!) and always tries to understand domain knowledge based on his project experience as much as possible.● Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as big data, data science, machine learning, and Cloud computing. Over the past few years, they have worked with some of the World's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the World's most popular soft drinks companies, helping each of them to better make sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.● Jim DiLorenzo is a freelance programmer and Reinforcement Learning enthusiast. He graduated from Columbia University and is working on his Masters in Computer Science. He has used TRFL in his own RL experiments and when implementing scientific papers into code.
