Fundamentals of Machine Learning with Scikit-Learn
A tutorial video (2 hours) derived from the book Machine Learning Algorithms has been released: Fundamental of Machine Learning with Scikit-Learn:
From the notes:
As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine Learning applications are everywhere, from self-driving cars, spam detection, document searches, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and data science. The main challenge is how to transform data into actionable knowledge.
In this course you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are: Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, and Feature engineering. In this course, you will also learn how these algorithms work and their practical implementation to resolve your problems.
Link to the publisher page: https://www.packtpub.com/big-data-and-business-intelligence/fundamentals-machine-learning-scikit-learn-video
My latest machine learning book has been published and will be available during the last week of July. From the back cover: In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science.