In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn't contain any hard math - just straight up coding in Python. All the materials for this course are FREE. After a brief discussion about what NLP is and what it can do, we will begin building very useful stuff. The first thing we'll build is a spam detector.

About this course: If you want to break into competitive data science, then this course is for you! Participating in predictive modelling competitions can help you gain practical experience, improve and harness your data modelling skills in various domains such as credit, insurance, marketing, natural language processing, sales' forecasting and computer vision to name a few. At the same time you get to do it in a competitive context against thousands of participants where each one tries to build the most predictive algorithm. Pushing each other to the limit can result in better performance and smaller prediction errors. Being able to achieve high ranks consistently can help you accelerate your career in data science.

Organizations are teams of teams. By definition, a manager gets work done not only through one's own resources and efforts, but also through others. In other words, you are required to work effectively with people outside your team. These are individuals and groups within the organization and also outside. You have to influence people at different levels and functions, build collaborative relationships wherever possible, negotiate wisely, handle difficult conversations and make decisions in the face of uncertainty and complexity.

R is a data analysis tool, graphical environment, and programming language. Without any prior experience in programming or statistical software, this video tutorial will help you quickly become a knowledgeable user of R. Now is the time to take control of your data and start producing superior statistical analysis with R. In this video tutorial, you will start with a quick refresher on programming in R. You will learn to set up your R development environment, as well as work on a few simple R programs. After that you will dive right into working with different types of data structures in R, such as vectors, lists, matrices, etc. You will explore how to import and export data for your data analysis project, and also connect to databases such as PostgreSQL.

Machine learning is the subfield of computer science that gives computers the ability to learn without being explicitly programmed. It explores the study and construction of algorithms that can learn from and make predictions on data. The R language is widely used among statisticians and data miners to develop statistical software and data analysis. Machine Learning is a cross-functional domain that uses concepts from statistics, math, software engineering, and more. In this course, you'll get to know the advanced techniques for Machine Learning with R, such as hyper-parameter turning, deep learning, and putting your models into production through solid, real-world examples.

Are you interested in learning about R Programming? Are you interested in learning about data analysis and machine learning, but don't know where to start? Are you interested in sports and curious to know how analytics can be applied to sports? In the game of football, are you curious to know which positions are the most important? If so, you've come to the right course!

Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. That's why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments. New posts will be published here first, and previous posts are archived on the Udacity blog.

Andrew Ng thinks a lot about getting machines ... to think for us. He was the founder of the artificial intelligence research project Google Brain. And his latest company is called Landing.AI. The startup has partnered with the electronics manufacturing giant Foxconn, as well as other companies in Japan, Taiwan, and mainland China to bring more AI into the manufacturing space. Ng says that AI has the potential to revitalize the factory floor.

About this course: The value of IoT can be found within the analysis of data gathered from the system under observation, where insights gained can have direct impact on business and operational transformation. Through analysis data correlation, patterns, trends, and other insight are discovered. Insight leads to better communication between stakeholders, or actionable insights, which can be used to raise alerts or send commands, back to IoT devices. With a focus on the topic of Exploratory Data Analysis, the course provides an in-depth look at mathematical foundations of basic statistical measures, and how they can be used in conjunction with advanced charting libraries to make use of the world's best pattern recognition system – the human brain. Learn how to work with the data, and depict it in ways that support visual inspections, and derive to inferences about the data.

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