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Aspiring scientist in the field of Artificial general intelligence based on Reinforcement Learning. Currently graduate student focused in Machine Learning. My research interest and goals are aligned with the broader family of machine learning towards scalable deep learning, Bayesian optimization, probabilistic learning, meta-learning, representation learning, Bayes' theorem, computer vision, deep reinforcement learning and robotics. PhD in process. Soon, find a copy of my research proposal here. Plus, I will be releasing a mathematics paper here in three parts (Linear Algebra, Calculus & Multivariate Calculus and statistics and probability) which will cover all fundamentals for Machine Learning. If you are keen to learn all essential mathematics for Machine learning click github below where you can find all materials to get your hands dirty.
Email / CV / Podcast / Google Scholar / Twitter / Github / Medium / Proposal / |
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Deep Reinforcement Learning, Deep Neural Network, deep probabilistic model, bayesian optimization, computer vision, robotics, meta-learning, Multi-agent Learning, etc..I am trying to understand how brain/mind works by exploring and building more and more intelligent systems or agents that learn from experience and transfer knowledge to various other domains. My long term goal is to build an intelligent system in a way that is capable of doing a wide range of tasks that can do a full spectrum of cognitive tasks at a human level. Representative papers are highlighted. |
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In progress |
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Feel free to steal source code for this website's from source code. Also, consider using Leonid Keselman's Jekyll fork of this page. |