Optimization is a field of mathematics concerned with finding a good or best solution among many candidates. It is an important foundational topic required in machine learning as most machine learning algorithms are fit on historical data using an optimization algorithm. Additionally, broader problems, such as model selection and hyperparameter tuning, can also be framed […]
In this post, we will take a tour of the most popular machine learning algorithms. It is useful to tour the main algorithms in the field to get a feeling of what methods are available. There are so many algorithms that it can feel overwhelming when algorithm names are thrown around and you are expected to […]
It can be difficult to get started in deep learning. Thankfully, a number of universities have opened up their deep learning course material for free, which can be a great jump-start when you are looking to better understand the foundations of deep learning. In this post you will discover the deep learning courses that you […]
There are a lot of machine learning tools out there. Which ones should you use? What tools could actually be useful on your project? Choosing a tool is a big deal. The tools that you use for machine learning determine the results you can achieve. It is critical that you take the time to choose […]
What are the basic concepts in machine learning? I found that the best way to discover and get a handle on the basic concepts in machine learning is to review the introduction chapters to machine learning textbooks and to watch the videos from the first model in online courses. Pedro Domingos is a lecturer and professor on machine […]
You want to learn machine learning or data science. You might want a job or the opportunity to get a job in machine learning or data science. Alternatively, you might be a student or in a data role and looking to accelerate your learning in the area. If you think your only options are to […]
Colorado Reed from Metacademy wrote a great post recently titled “Level-Up Your Machine Learning” to answer the question he often receives of: What should I do if I want to get ‘better’ at machine learning, but I don’t know what I want to learn? In this post you will discover a summary of Colorado recommendations […]
In this post I lay out a concrete self-study roadmap for applied machine learning that you can use to orient yourself and figure out your next step. I think a lot about frameworks and systematic approaches (as evidenced on my blog). I would consider this post a vast expansion of my previous thoughts on a self-study […]
