For those who already have a basic understanding of machine learning, you should start with the advance machine learning videos. These videos will introduce you to various machine learning libraries, modeling techniques and other advanced concepts of machine learning. It covers theoretical & practical concepts on supervised, unsupervised and deep learning algorithms. It will introduce you to sentimental analysis, recommendation system, predicting stock prices, create neural network using python & tensorflow and introduction to genetic algorithms.
The scikit-learn library is one of the most popular platforms for everyday machine learning and data science. The reason is because it is built upon Python, a fully featured programming language. But how do you get started with machine learning with scikit-learn. Kevin Markham is a data science trainer who created a series of 9 videos that show you exactly how to get started in machine learning with scikit-learn. In this post you will discover this series of videos and exactly what is covered, step-by-step to help you decide if the material will be useful to you.
Sure, there are lots of tutorials and overviews on gaining the insight you need into picking up machine learning, but many (most?) of them take the long view: get a foundation first, learn the basics next, then learn a bit of complementary theory before getting too far ahead of yourself in practical terms, take a step back, try your hand at a few examples, undertake a project on your own... This is all great advice, and a great approach to learning... well, almost anything. But let's say you're not starting from scratch. Or you don't have the patience to go through all of the motions. Let's say you want to hit the ground running and scramble under pressure to learn everything right now.
Machine learning is the predictive heart of big data analytics, and one of the key skills that separates data scientists from mere analysts. But getting started with machine learning can be a challenge. Here are a few ways beginners can get off the ground with their machine learning adventure. Machine learning is a vast field with many different specialties, so it's quite easy for a beginner to get overwhelmed. For instance, one specialty called deep learning powers many of today's artificial intelligence breakthroughs.