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.

Thank you all for the huge response to this emerging course! We are delighted to have over 2300 students in over 102 different countries and for the overwhelmingly positive and thoughtful reviews. It's such a privilege to share this important topic with everyday people in a clear and understandable way. In this introductory course, the "Backyard Data Scientist" will guide you through wilderness of Machine Learning for Data Science. Accessible to everyone, this introductory course not only explains Machine Learning, but where it fits in the "techno sphere around us", why it's important now, and how it will dramatically change our world today and for days to come. We'll then explore the past and the future while touching on the importance, impacts and examples of Machine Learning for Data Science: To make sense of the Machine part of Machine Learning, we'll explore the Machine Learning process: Our final section of the course will prepare you to begin your future journey into Machine Learning for Data Science after the course is complete.

Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. This video will arm you with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation. You will learn to use the Flask framework for Restful APIs.

Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more! Are you ready to start your path to becoming a Data Scientist! This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!

Go hands-on with the neural network, artificial intelligence, and machine learning techniques employers are seeking! Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. If you've got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry - and prepare you for a move into this hot career path. This comprehensive course includes over 80** lectures** spanning 12** hours of video**, and most topics include hands-on Python code examples you can use for reference and for practice. I'll draw on my 9 years of experience at Amazon and IMDb to guide you through what matters, and what doesn't.

Here's a list of some of the best Chatbot tutorials, courses, videos and books to help you learn Chatbots in 2018. ChatBots: How to Make a Facebook Messenger Chat Bot in 1hr by Stefan Kojouharov will help you build a Chat Bot for Facebook Messenger. This is a step by step guide in building a chatbot for Facebook Messenger. You will learn the main components of building a chatbot. This includes building the chatbot server, adding your code, deploying your chatbot to the cloud, and connecting it with Facebook Messenger.

Each module of the course starts with theory to explain upcoming concepts. Next, students see how this theory is put into practice as we do a code walk through. The course focuses on building procedural machine learning processes from the ground up. Although algorithms from various libraries are used. Writing all of the processing from scratch allows students to better understand what is involved when processing data.

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.

It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to both statistical and machine learning regression analysis. However, majority of the course will focus on implementing different techniques on real data and interpret the results. After each video you will learn a new concept or technique which you may apply to your own projects.

Get the foundation in business analysis you need to solve your organization's biggest problems. This course provides everything you need to get started in your career in business analysis. Our courses focus on how analysis is performed in the real world, and they're full of examples, case studies and lessons learned from actual Business Analysts on the job. This is a perfect first course in any business analysis curriculum.