Machine learning gives you unimaginably powerful insights into data. Today, implementations of machine learning have been adopted throughout Industry and its concepts are numerous. This video is a unique blend of projects that teach you what Machine Learning is all about and how you can implement machine learning concepts in practice. Six different independent projects will help you master machine learning in Python. The video will cover concepts such as classification, regression, clustering, and more, all the while working with different kinds of databases. By the end of the course, you will have learned to apply various machine learning algorithms and will have mastered Python's packages and libraries to facilitate computation. You will be able to implement your own machine learning models after taking this course.
Style and Approach This video is a combination of six independent projects, each taking a unique dataset, a different problem statement, and a different solution.
Table of Contents BUILD AN APP TO FIND CHEAP AIRFARES FORECAST THE IPO MARKET USING LOGISTIC REGRESSION CREATE A CUSTOM NEWSFEED FORECASTING THE STOCK MARKET WITH MACHINE LEARNING BUILD AN IMAGE SIMILARITY ENGINE BUILDING A CHATBOT
What You Will Learn Explore and use Python's impressive machine learning ecosystem Successfully evaluate and apply the most effective models to problems Learn the fundamentals of NLP-and put them into practice Visualize data for maximum impact and clarity Deploy machine learning models using third-party APIs Get to grips with feature engineering
Authors Alexander T. Combs Alexander T. Combs is an experienced data scientist, strategist, and developer with a background in financial data extraction, natural language processing and generation, and quantitative and statistical modeling. He is currently a full-time lead instructor for a data science immersive program in New York City.