NLP, or Natural Language Processing, is a computational approach to communication. This course will get you up-and-running with the popular NLP platform called Natural Language Toolkit (NLTK) in no time. You will start off by preparing text for Natural Language Processing by cleaning and simplifying it. Then you will implement more complex algorithms to break this text down and uncover contextual relationships that reveal the meaning and content of the text. You will learn how to tokenize various parts of sentences, and how to analyze them.

This course is about the fundamental concepts of machine learning, facusing on neural networks. This topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detect cancer for example. We may construct algorithms that can have a very very good guess about stock prices movement in the market. In the first chapter we are going to talk about the basics of the R programming language.

In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.

In SQL Server 2016, you have to the ability to integrate R for in-database, scalable machine learning. We will explore some of the challenges faced when pushing your algorithms and results to a consumable format. This is the first course in a series of courses to be released.

Natural Language Processing is used in many applications to provide capabilities that were previously not possible. It involves analyzing text to obtain the intent and meaning, which can then be used to support an application. Using NLP within an application requires a combination of standard Java techniques and often specialized libraries frequently based on models that have been trained. If you're interested to learn the powerful Natural Language Processing techniques with Java, then go for this Learning Path. Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

Artificial Intelligence is a fascinating topic and also a kind of buzzword which has been there for years and will dominate for many more years. As and when I interact with developers and students I hear different intuitions about machine learning, deep learning and AI. Sometimes, there's also a confusion whether AI, ML & DL are all the same or different from each other. So, I use this infographic in my first slide of a presentation. As humans, we all are different and our way of learning is also differs.

Machine learning is a way for a program to analyze previous data (or past experiences) to make decisions or predict the future. Wow, that sounds pretty complex! But aren't you claiming everyone can do it? We use frameworks like TensorFlow that make it easy to build, train, test, and use machine learning models. All you need to know is a little Python, which we will teach you, of course. TensorFlow has really been a saving grace.

It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your research as experienced investor. Learning pairs trading analysis is indispensable for finance careers in areas such as quantitative research, quantitative development, and quantitative trading mainly within investment banks and hedge funds. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors quantitative trading research and development. But as learning curve can become steep as complexity grows, this course helps by leading you step by step using MSCI Countries Indexes ETF prices historical data for back-testing to achieve greater effectiveness.

Learn to carry out pre-processing, visualization and machine learning tasks such as: clustering, classification and regression in R. You will be able to mine insights from text data and Twitter to give yourself & your company a competitive edge. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals.

Salesforce has done it again. They are taming the complexity of Artificial Intelligence, enabling you to make massive amounts of decisions and discover patterns in reams of data, all with clicks instead of code. This course is for the absolute beginner to Artificial Intelligence (AI), Machine Learning, Deep Learning, and Data Science. If you are feeling overwhelmed by either the tsunami of data that you are tasked with trying to make sense out of, or overwhelmed by the tsunami of media coverage around Artificial Intelligence, Deep Learning, Data Science, and Machine Learning, I am here to share a competitive advantage. There is an AI and Data Discovery platform that can be constructed and configured with clicks instead of code.