This is a collection of free resources beyond the regularly shared books, MOOCs, and courses, mostly from over the past year. They start from zero and progress accordingly, and are suitable for individuals looking to pick up some of the basic ideas, before hopefully branching out further (see the final 2 resources listed below for more on that).
These resources are not presented in any particular order, so feel free to pursue those which look most enticing to you. All credit goes the the individual authors of the respective materials, without whose hard work we would not have the benefit of learning from such great content.
5 Fantastic Practical Machine Learning Resources
Interested in getting running with machine learning?
For many good reasons, much of the highest quality machine learning educational resources tend to have a very strong focus on theory, especially at the beginning. There seems, however, to be an increasing trend of getting on to the practical from the start, and mixing practice and theory along the way as resources progress. This post presents 5 such resources.
Covering machine learning right from basics, as well as coding algorithms from scratch and using particular deep learning frameworks, these resources cover quite a bit of ground. They are also all free, so get reading, get watching, and get coding.
5 Free Resources for Furthering Your Understanding of Deep Learning
Interested in furthering your understanding of neural networks and deep learning, above and beyond the basic introductory tutorials and videos out there? This post includes 5 specific video-based options for doing just that, collectively consisting of many, many hours of insights. If you already possess some basic knowledge of neural networks, it may be time to jump in and tackle some more advanced concepts.
5 Fantastic Practical Natural Language Processing Resources
Are you interested in some practical natural language processing resources?
There are so many NLP resources available online, especially those relying on deep learning approaches, that sifting through to find the quality can be quite a task. There are some well-known, top notch mainstay resources of mainly theoretical depth, especially the Stanford and Oxford NLP with deep learning courses:
- Natural Language Processing with Deep Learning (Stanford)
- Deep Learning for Natural Language Processing (Oxford)
But what if you've completed these, have already gained a foundation in NLP and want to move to some practical resources, or simply have an interest in other approaches, which may not necessarily be dependent on neural networks? This post (hopefully) will be helpful.
5 Free Resources for Getting Started with Deep Learning for Natural Language Processing
Interested in applying deep learning to natural language processing (NLP)? Don't know where or how to start learning?
This is a collection of 5 resources for the uninitiated, which should open eyes to what is possible and the current state of the art at the intersection of NLP and deep learning. It should also provide some idea of where to go next. Hopefully this collection is of some use to you.
5 Free Courses for Getting Started in Artificial Intelligence
Looking for an introductory graduate school AI regimen from materials freely available online? With more and more institutes of higher learning today making the decision to allow course materials to be openly accessible to non-students via the magic of the web, all of a sudden a pseudo-university course experience can be had by almost anyone, anywhere. Have a look at the following free course materials, all of which are appropriate for an introductory level of AI understanding, some of which also cover niche application concepts and material.
Some of these professors and their material shared below have been instrumental in shaping the minds of top AI researchers and practitioners in the world. There is no reason you cannot benefit from this same material and instruction on your own.
5 Free Resources for Getting Started with Self-driving Vehicles
Interested in self-driving vehicles? Don't know where or how to start learning?
Formal education in this topic is sparse, and so those interested in learning must do so with a hacker mentality. I have collected a short list of 5 resources to help newcomers find their bearings, all of which are free. Hopefully it is useful to some.
- Natural Language Processing Nuggets: Getting Started with NLP
- 5 Machine Learning Projects You Should Not Overlook, June 2018
- DIY Deep Learning Projects