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.

What is machine learning / ai? How to lean machine learning in practice? Machine learning and neural networks are got a lot of attention recently. Self driving cars, predictive analytics and other highly advanced topics are closely related to those topics. Therefore it's of the utmost of importance to familiarize oneself with machine learning and neural networks.

They are powerful data mining techniques that allow you to detect patterns in your data or variables. For each technique, a number of practical exercises are proposed. By doing these exercises you'll actually apply in practice what you have learned. This course is your opportunity to become a machine learning expert in a few weeks only! With my video lectures, you will find it very easy to master the major machine learning techniques. Everything is shown live, step by step, so you can replicate any procedure at any time you need it. So click the "Enroll" button to get instant access to your machine learning course. It will surely provide you with new priceless skills. And, who knows, it could give you a tremendous career boost in the near future.

The best job to have in 2017 according to Glassdoor? The #1 skill you need to start a career in Data Science? So, if you are interested in a career in data science, algorithmic trading, robotics, or any industry where human labor is getting replaced by machines, you have come to the right place! We have prepared an amazing course not only to get you acquainted with, but help you understand how deep machine learning works! Worried you have no experience?

About this course: This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. This is the fourth course of the Deep Learning Specialization.

Want to know how Machine Learning algorithms work and how people apply it to solve data science problems? You are looking at right course! This course has been created, designed and assembled by professional Data Scientists who have worked in this field for nearly a decade. We can help you understand the complex machine learning algorithms while keeping you grounded to the implementation on real business and data science problems. We will let you feel the water and coach you to become a full swimmer in the realm of data science and Machine Learning.

You learn important information on a daily basis, either to gain knowledge or for school, but you are losing a lot of this useful information because you didn't learn it properly in the first place It doesn't have to stay this way. My complete Learning Strategy & Speed Reading course will show you the exact techniques and strategies you need to learn the right way and gain knowledge or remember important information easily. For less than a movie ticket, you will get over 4 hours of video lectures and the freedom to ask me any questions regarding the course as you go through it. What Is In This Course? Your Learning and Reading Sessions Will Never Be The Same.

Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This video will teach you all it takes to perform complex statistical computations required for Machine Learning. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. We will discuss the application of frequently used algorithms on various domain problems, using both Python and R programming.

About this course: How can we create agile micro aerial vehicles that are able to operate autonomously in cluttered indoor and outdoor environments? You will gain an introduction to the mechanics of flight and the design of quadrotor flying robots and will be able to develop dynamic models, derive controllers, and synthesize planners for operating in three dimensional environments. You will be exposed to the challenges of using noisy sensors for localization and maneuvering in complex, three-dimensional environments. Finally, you will gain insights through seeing real world examples of the possible applications and challenges for the rapidly-growing drone industry. Mathematical prerequisites: Students taking this course are expected to have some familiarity with linear algebra, single variable calculus, and differential equations.

In this lecture, we will learn how to predict an outcome that can have multiple values. We are going to use the wine quality dataset and predict the quality of wine based on various characteristics or physiochemical properties of wine, that may affect its quality, such s the acidity, citric acid, residual sugar in it, density and so on.