This course will get you started in building your FIRST artificial neural network using deep learning techniques. Following my previous course on logistic regression, we take this basic building block, and build full-on non-linear neural networks right out of the gate using Python and Numpy. All the materials for this course are FREE. We extend the previous binary classification model to multiple classes using the softmax function, and we derive the very important training method called "backpropagation" using first principles. I show you how to code backpropagation in Numpy, first "the slow way", and then "the fast way" using Numpy features.

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 make business forecasting related decisions. Learning regression machine learning is indispensable for data mining applications in areas such as consumer analytics, finance, banking, health care, science, e-commerce and social media. It is also essential for academic careers in data mining, applied statistical learning or artificial intelligence. And it is necessary for any business forecasting related decision. But as learning curve can become steep as complexity grows, this course helps by leading you through step by step real world practical examples for greater effectiveness.

Source code (with copious amounts of comments) is attached as a resource with all the code-alongs. 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.

In this video course, we start by focusing on R's similarities with programming languages such as basic/C/C# with loops and conditional tests like if, so that you can feel at home and be productive straight away. We begin by introducing R and setting things up so that you are ready to go using Rstudio, the associated IDE. Then we look at R as a programming language and see how the standard things are done in it, so you can see that it's not that different from other programming languages. Next, we introduce some R commands, which are very useful and not as common in traditional languages since manipulating data is more important in R. Moving on, we look at an example in the Titanic dataset, which is the kind of thing you'll come across in R, a multidimensional collection of variables of different types. Using the tools that we cover we can form a picture, a story behind the data.

I am from Budapest, Hungary. I am qualified as a physicist and later on I decided to get a master degree in applied mathematics. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation.

You can now purchase an Xbox One X. Microsoft has opened pre-orders for the upcoming 4K console, which the company describes as "the world's most powerful console". The Xbox One X was officially unveiled in June, and will come out on 7 November. It costs £449, and is claimed to be 40 per cent more powerful than any other console on the market. Microsoft has also launched a special version of the Xbox One X, called the Project Scorpio Edition. Project Scorpio was the One X's codename, and the company wants it to "live on" and enable fans "to celebrate both our heritage and the power and precision that we are bringing into our future". It's exactly the same as the standard Xbox One X, but the words "Project Scorpio" are printed on both the console and the controller, and it comes with an exclusive vertical stand.

If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you'll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We're approaching a new era where only apps and games that are considered "smart" will survive.

From personal experience, read as many of these as you can, maybe more than once. Yes, some will be better than others but the more you read different explanations and see different diagrams the more you will "get it". Also, it's not either or, read these and do the coursera course.

Are you currently enrolled in either of my Core or Intermediate Spatial Data Analysis Courses? Or perhaps you have prior experience in GIS or tools like R and QGIS? You don't want to spend 100s and 1000s of dollars on buying commercial software for imagery analysis? The next step for you is to gain profIciency in satellite remote sensing data analysis. MY COURSE IS A HANDS ON TRAINING WITH REAL REMOTE SENSING DATA WITH OPEN SOURCE TOOLS!

This course not only covers machine learning techniques, it also covers in depth the rationale of investing strategy development. This course is the first of the Machine Learning for Finance and Algorithmic Trading & Investing Series. If you are looking for a course on applying machine learning to investing, the Machine Learning for Finance and Algorithmic Trading & Investing Series is for you. With over 30 machine learning techniques test cases, which included popular techniques such as Lasso regression, Ridge regression, SVM, XGBoost, random forest, Hidden Markov Model, common clustering techniques and many more, to get you started with applying Machine Learning to investing quickly.