Machine learning has been one of the most prominent buzzwords in recent years. Some people say the term in hushed tones, the fear of a robot takeover filling their minds, while others are positively giddy at the prospect. The reality is both more mundane and more promising than either of these two groups would assume. Often used interchangeably with the term “artificial intelligence”, machine learning is all about using predictive algorithms to make life easier. Think about fridges that tell you when you’re out of food, Roombas that know where to clean, and self-driving cars that actually minimize the chance of a collision. It’s a huge improvement in the quality of life, and that is always in demand. Many companies are already using machine learning to their advantage, so staying on top of the latest trends is the best way to ensure that your business is future-proof. We realize that the inner workings of machine learning may be complex and intimidating if you just dive deep into them without preparation, which is why we’ve compiled this list of blogs and resources. Since Python is very often the soil from which machine learning can grow, you can say we know a thing or two about the topic. Read on to learn where to start your machine learning adventure and how to stay up to date.
Blogs
1. KDnuggets
One of the longest-running and most popular blogs on the topic of machine learning to this day. The fact that it’s still so widely frequented despite the fact that its user interface looks like it was there when the wheel was invented just goes to show that function really trumps form in the long run. Updated regularly with rich, informative content, KDnuggets has guides for beginners as well as intermediate users, alongside information on various courses and events that can bring you up to speed on all things machine learning.
Notable post: The Beginner’s Guide to Data Integration Approaches in Business Intelligence is a great example of how KDnuggets’ writers explain specific machine learning-related concepts alongside their practical implementations.
2. Algorithmia
https://algorithmia.com/bloghttps://algorithmia.com/blogEDX
If you’re looking for a blog that will give you a good rundown of everything related to machine learning, Algorithmia is a good starting point. These Seattle-based experts have quite vast reserves of knowledge that they happily share in digestible blog posts. They will help you learn about the most basic aspects of artificial intelligence as well as more advanced concepts.
Notable post: Machine learning examples is a very thorough post that does a good job of introducing the concept of machine learning to an entry-level reader. As the title suggests, it lists real-life examples of practical machine learning implementations.
3. Medium
https://medium.com/topic/machine-learningMachine Learning Crash Course
Medium hosts a large number of informative blogs, and its machine learning section is particularly helpful. What you’ll notice right away is the light, familiar tone, as exemplified by articles such as How I Accidentally Created an Infinite Pixel Hellscape, but don’t let that immediate impression fool you into thinking that’s all there is to it. With frequently published articles written both by amateur programmers and industry experts, you’ll find a healthy dose of tips based on real, practical knowledge, providing answers to the most pressing questions you may have on all things machine learning.
Notable post: The Story of How AI changed Google Maps is an extensive take on the influence machine learning has had on the popular app. It’s a fascinating read, showcasing exactly how the technology in question can make a big impact.
4. Towards Data Science
https://towardsdatascience.com/Pandas
Hosted by Medium, Towards Data Science features plenty of high-quality articles written by contributors from all round the world. A dedicated team of international experts works on reviewing the content written by the community to ensure that every single piece that gets published is worth your time. You’ll find entire sections dedicated to machine learning and AI, each of them filled to the brim with highly educational content.
Notable post: This tutorial on how to build an app that generates photorealistic faces is a great example of Towards Data Science’s approach. The article is practical, digestible, and well-researched.
5. Distill
Calling this entry a blog is an understatement. Distill an online research journal that provides info on some of the latest developments in machine learning. What this entails is that the content here will be a bit more advanced, certainly beyond entry-level, but it is nonetheless presented in an accessible way. Of particular note are the graphics, with advanced yet clear reactive diagrams perfectly illustrating the sometimes confusing processes described in the articles.
Notable post: One of the best recent posts that drive the point home that the graphics make all the difference is one that deals with the visualization of neural networks. The various graphs and charts found throughout do a good job of making this complicated matter much easier to understand.
6. DeepMind’s Blog
https://distill.pub/Elements of AI
If you’re looking for experts on the topic, it’s best to look for those who deal with it on a daily basis. DeepMind is a British AI company, currently owned by Google. Their posts are mostly reports and think pieces related to their current research, so by following the blog closely you might learn a few things no one else is talking about yet. If you’re tired of reading and would prefer to listen to something instead, they also have podcasts.
Notable post: Thanks to DeepMind’s blog you get to see exactly how AI can change the world through its practical implementation. Their post on WaveNet technology and how it can help speech-impaired people restore their old voices gives you a glimpse into the potential of machine learning to improve lives.
7. The TensorFlow Blog
https://www.tensorflow.org/Quora
If you’ve already gotten your feet wet and are ready for deeper waters, Tensorflow is the place to go. The blog section is incredibly technical, definitely not for absolute neophytes, but even if you’re more familiar with the topic and are looking for more specific knowledge that will help you hone your machine learning skills, this is the blog for you. It also offers courses with certificates to boost your business’s credibility in the field.
Notable post: An article on WebAssembly backend for TensorFlow.js not only explains the concept itself but also provides detailed instructions on how you can use the WASM backend to your advantage.
8. PyImageSearch
https://www.pyimagesearch.com/blog/
Libraries are an important element of machine learning, but how exactly do you use them? PyImageSearch offers a lot of case studies and practical examples that will help you learn all about libraries at a pace you’re comfortable with. The tutorials on the blog can get pretty detailed and they are some of the best sources of information about libraries.
Notable post: A good example of these tutorials is the guide on OpenCV’s “dnn” module with NVIDIA GPUs, CUDA and cuDNN. Reading through this piece you can see how specific these tutorials can get. The blog post itself goes into very deep detail on each step of the procedure, so that by the end of it you know exactly how to deal with the problem in question.
9. O’Reilly
https://www.oreilly.com/radar/topics/ai-ml/
With O’Reilly’s blog, it’s easy to stay on top of the industry trends as their posts often come from leading influencers. It will help you understand how artificial intelligence and machine learning are implemented by businesses, giving you the inspiration and tools you need to make sure your business remains relevant.
Notable post: A perfect example is their article on 5 key areas for tech leaders to watch in 2020. It provides a clear picture of all the current trends and how they should influence your operations.
Other resources
1. Kaggle
Perhaps machine learning sounds like a great tool for you, but you’re not exactly willing to spend time learning it from the ground up. You want to take advantage of it as a company, however, so you’re still going to need some experts to handle it for you. Luckily, Kaggle is here to help you out with just that. Many experts who started out by providing their services through Kaggle have gone on to set up their own companies in the field, making this site a veritable breeding ground for talent. You can get involved by organizing competitions, ensuring that the code and datasets you get are created with the greatest amount of precision.
2. EDX
EDXhas amassed an impeccable selection of courses for all machine learning enthusiasts, regardless of whether they’re just starting out or have advanced knowledge. EDX can help you join courses hosted by some of the most prestigious institutions in the world and point you in the direction of the most reputable resources.
3. Machine Learning Crash Course
https://developers.google.com/machine-learning/crash-course/ml-intro
What better place to learn all about machine learning than at the source. Google’s crash course is exactly what it says on the tin, but that doesn’t even begin to cover the sheer utility of this resource. It’s very neatly divided into units that are composed of several guides in video or text form, as well as practical activities. They come with a time estimation to give you flexibility in terms of deciding when and how you study.
4. Pandas
If you’re looking for libraries to get started with your machine learning endeavors, Pandas is definitely worth a look. Based on Python, Pandas began development in 2008. Since then, it’s been a reliable open-source library boasting many useful features, such as fast and efficient DataFrame object data manipulation, greatly optimized performance, and incredible flexibility. It’s perfect for both academic and commercial purposes.
5. Practical Machine Learning with Python
https://www.youtube.com/watch?list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v&v=OGxgnH8y2NM
Hosted by sentdex, this series of YouTube videos provides a comprehensive overview of machine learning and its practical applications. The course requires knowledge of Python, but you’ll learn everything else you need to know along the way. It’s the perfect guide that’s both digestible and exhaustive if you’re looking for something in a video format.
6. Elements of AI
https://course.elementsofai.com/
A crash course on AI that took Finland by storm is now available in a number of languages for free. With a pleasant design and short quizzes at the end of every course to test how much you’ve learned, this may just be one of the most accessible and effective courses you’ll take.
7. Quora
Quora has info on pretty much anything, often provided directly by experts in the field. AI is no exception in that regard: you’ll find a range of topics that will help you boost your grasp of the technology. With questions on machine learning, artificial intelligence, deep learning and more, all answered in one place, you have a handy source of instant knowledge.
8. Reddit
Much like Quora, Reddit pretty much has a subreddit for everything. While they’re not as extensive as Quora’s topics, Reddit is a community that will help you figure things out on your own, as well as provide bespoke guides for very obscure things. You can start with r/MachineLearning, r/artificial, and r/learnmachinelearning, to name just a few.
Final thoughts
It’s no secret that machine learning is the future, and gaining an understanding of it might determine whether your business will succeed.
Thankfully, the topic is endlessly fascinating, and knowledge that could potentially be world-changing is available to you in digestible forms. Even if you’re already familiar with machine learning, the rapid pace at which this field is expanding means that there’s always something new and exciting to learn.
Treat our list as your starting point, regardless of whether you’re at the beginning of your machine learning journey or you’re after more advanced resources.
While you’re at it, why not check out our articles about machine learning?
- Machine Learning Applications: 22+ Examples Across 4 Industries
- Will Artificial Intelligence Replace Programmers?
- Tutorial: Getting Started with Machine Learning in Python
- What Do Experts Say About the Future of Machine Learning (and Python)?
And if you have any questions, feel free to drop us a line.
