Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. 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.

From MOOCs (Massive open online courses) to the use of iPads in schools, there's no doubt that technology is changing the way that we learn. Chatbots could have a similar effect, too -- by offering a means by which children can better interact with the subjects they're studying. That was the conclusion reached by UK-based tech company rehabstudio. During a recent hackathon event, they came up with the idea of creating an "edubot" that would enable kids to ask questions to a tyrannosaurus rex (called Tina) using Facebook Messenger. The finished product was a collaboration between rehabstudio (providing the tech) and National Geographic Kids (providing the data.)

One day we will "think about machine learning the way we think about electricity: It's hard to imagine the world without it," said SAP Chief Innovation Officer Juergen Mueller at the recent SAP TechEd Barcelona. Under Mueller, SAP has embarked on a journey to bring machine learning to business around the world, essentially "electrifying" all applications with this technology. For the uninitiated, machine learning takes Big Data, runs it against sophisticated algorithms and helps applications to learn from this information. Massively improved computing power makes this possible in real time. Most importantly, it allows applications to "think" and independently resolve problems – going beyond what they were explicitly programmed to do, and often what humans can do.

Edtech, from artificial intelligence to cloud computing and augmented reality, is sweeping through the higher education sector. And as online learning providers continue to challenge the oldest and best-known institutions, the world's top business schools are racing to adopt cutting-edge learning technologies. "Innovations by vendors have led to the use of more advanced technologies such as simulations, cloud-based solutions, and AR," says Jhansi Mary, lead analyst at Technavio, the consultancy. At the forefront of the innovation wave is artificial intelligence, which has already permeated social media, stock picking and even transport. Advocates say AI can be applied in education through the tracking of students, to predict and optimize learning and performance.

This course aimed at students with beginner to intermediate skill in F#, basic understanding of the F# syntax and a light functional understanding would be beneficial. You'll also need a computer with Linux, OSX or Windows with F# installed and an internet connection. Have you wanted to understand how to'do' machine learning or implement algorithms from a textbook in a programming language, or deploy a library to Nuget? Well, this course includes sections on machine learning using a mathematical theorem known as Bayes' Theorem. We will start by creating a predictive text engine and deploy it to Nuget, while learning how to write some basic unit tests in FsUnit.

This team has decades of practical experience in working with Java and with billions of rows of data. If you are an analyst or a data scientist, you're used to having multiple systems for working with data. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code. Scala: Scala is a general purpose programming language - like Java or C . It's functional programming nature and the availability of a REPL environment make it particularly suited for a distributed computing framework like Spark. Analytics: Using Spark and Scala you can analyze and explore your data in an interactive environment with fast feedback.

But when is the last time you saw someone building a house with a hammer, a hand saw and some 2x4s? When you build a house, you need the right tools and materials to build a house. The basic ingredients for learning are neurons and myelin. Each time you fire a set of neurons while learning, they get wrapped in another thin layer of myelin, which is like insulation on an electric cord. The more the neurons get wrapped up, the faster the neurons can send signals.

Prerequisites: Working knowledge of Python is necessary if you want to run the source code that is provided. Basic knowledge of machine learning, especially ML classification techniques, would be helpful but it's not mandatory. Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce. Completely Practical: This course has just enough theory to get you started with both Quant Trading and Machine Learning.

Between the four of us, we have studied at Stanford, IIM Ahmedabad, the IITs and have spent years (decades, actually) working in tech, in the Bay Area, New York, Singapore and Bangalore. We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Udemy! We hope you will try our offerings, and think you'll like them:-)

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.