This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong [...]
In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!
This course is the second part of a two-part course on how to develop Deep Learning models using Pytorch. In the first course, you learned the basics of PyTorch; in this course, you will learn how to build deep neural networks in PyTorch. Also, you will learn how [...]
Learn the principles of machine learning and the importance of algorithms. Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.
Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security [...]
In this course, the instructor will discuss the fundamental analysis of investment using R programming. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to do the elemental analysis for investment management [...]
This first course in this specialization is Exploring and Preparing your Data with BigQuery. Here we will see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud Platform. You’ll pick up some SQL along the way [...]
Мы будем учиться находить и оценивать зависимости в реальных данных, а также визуализировать, интерпретировать и использовать их для прогнозирования. We will learn to identify and estimate relationships in the real data, as well as visualize, interpret and apply them for making predictions.
In sports, gut instincts are great but data analytics are necessary. Learn how to use data, facts, and metrics to identify problems, make informed decisions and propose innovative solutions to guide strategic business decisions in the sport industry.
As a successful sales executive, you can help fans become part of the experience, both in the stadium and out. Learn key sales and revenue generation strategies from professionals within the sports industry, which is valued at more than $500 billion this year.