This book is aimed at senior undergraduates and graduate students in Engineering, Science, Mathematics, and Computing. It expects familiarity with calculus, probability theory, and linear algebra as taught in a first or second year undergraduate course on mathematics for scientists and engineers.
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This list tries to cover from basic introductory to deep analytical data science materials. You’ll also find various curriculums for learning Data Science. Foundational in both theory and technologies, the Open Source Data Science Masters (OSDSM) breaks down the core competencies necessary to making use of data. All kinds of topics will be covered, including Python, machine learning, specific topics such as statistics, databases, linear algebra / programming, etc., courses, tutorials and a long list of blogs which you can follow and refer to.
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With an exponentially growing community around data science, machine learning, AI, web dev and more, Python is a language that opens programming access to the world. The list goes on for why we think it’s a good idea to learn Python programming, whether you’re new to coding or an experienced dev. These resources will cover Django, Flask, Massive Open Online Courses (MOOC), Tutorials, other Python Resources and a list of websites in which you can test out your skills.
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The Masterclass provides a complete roadmap for building AI assistants—all the way from installing Rasa for the first time to deploying a finished project on Kubernetes. Along the way, we cover important machine learning concepts and practical coding examples to give you a solid foundation in conversational AI.
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Bruce Hajek is a professor of the department of electrical and computer engineering, research professor of coordinated science laboratory and hoeft chair of college of engineering at University of Illinois. His research interests include Communication Networks, Auction Theory (e.g. combinatorial auctions for sale of spectrum licenses), Stochastic Analysis, Combinatorial Optimization, Machine Learning, Information Theory and Bioinformatics.
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A 195-page monograph by a top-1% Netflix Prize contestant. Learn about the famous machine learning competition. Improve your machine learning skills. Learn how to build recommender systems.
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We have a list of the most knowledgeable, informative and entertaining free ebooks and resources being offered which you can enjoy from the comfort of your home. 177 of the best free resources from mathematics, computer stuffs, programming, crypto, economics, short stories, operating systems and many more.
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Any serious developer will need to learn how to program in order to really understand what is going on behind the curtain, or if you are curious to wonder about or query how your favorite program works. This is where programming tutorials come in. The following are 42 Free and Paid Programming Resources to Learn Web Development, covering 3 different levels – beginner, intermediate and expert resources.
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