While making GeekForge — a daily listing of interesting coding tasks — we researched several sources where you can learn AI and ML, and we thought it would be a good idea to share this list with you.
Two years have already passed since Mark Cuban said that if you don’t understand artificial intelligence, deep learning, and machine learning “you’re going to be a dinosaur within three years.” If you still didn’t dig yourself into that knowledge, especially if you’re a developer, then you’ve got about a year left to see whether he was right or not.
But luckily for you, if you are in fact interested in keeping your skills up to date, I hand-picked the best resources that are relevant today, regardless if you’re a beginner in the field or if you’ve already got your feet wet a long time ago. From video courses and books to interactive classes and coding tasks, within this list you will find the way to keep yourself out of the prehistoric era!
This one-hour course introduces the machine-learning mindset and helps you identify the appropriate situations for machine learning.
This prepares students to make meaningful contributions to society as engaged citizens and leaders in a complex world.
You can solve tasks independently or discuss them with the community. It’s the best way to educate yourself on new technology and build a portfolio of your completed tasks.
Materials on AI programming and ML (machine learning) introduce you to their applications to computational problems and understanding intelligence.
This course will introduce you to the basics of AI. Topics include machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
UC Berkeley was born out of a vision in the State Constitution for a university that would “contribute even more than California’s gold to the glory and happiness of advancing generations.”
Learn the fundamentals of AI and apply them. Design intelligent agents to solve real-world problems including search, logic, and constraint satisfaction problems.
This course includes interactive demonstrations that are intended to stimulate interest and to help students gain intuition about how artificial intelligence methods work under a variety of circumstances.
Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications.
This best-selling book offers the most comprehensive, up-to-date introduction on the theory and practice of artificial intelligence
Statistical approaches to processing natural language text have become dominant during the recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear.
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition.
This course explains why predictive analytics projects are ultimately classification problems, and how data scientists can choose the right strategy for their projects.
This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience.
This historical survey compactly summarizes relevant work on deep artificial neural networks, which have won numerous contests in pattern recognition and machine learning.
Grokking Deep Learning in Motion is a new live video course that takes you on a journey into the world of deep learning.
No matter what your prior experience is, the fact that you can learn the basics of the most important technologies in the world, like artificial intelligence and machine learning, to improve your coding skill set could place you above your peers in no time. Any of the following resources could be a starting point. Which one will it be for you? Ordering one of the books, enrolling in a university course, or maybe just signing yourself in for the daily tasks on GeekForge. Any of these options are better than doing nothing.
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