This is the second edition of my weekly update on deep learning. Every Thursday, I’ll release a new batch of research papers, blog posts, Github repos, etc. that I liked over the past week. Links are…

This course covers C from very basic to more advanced features.Maybe you have some experience with other programming languages, but want to learn C. It's a great language to add to your resume!.The object oriented programming concepts are clearly explained, you will learn classes, objects, inheritance, polymorphism, Operator overloading, Data Structure,Pointer, file handling,Dynamic Memory allocation,Recursion, apart from basic programming concepts like variables, branching and looping, functions, reference parameters, arrays, string,vectors hands on the real life project in C . The course will be constantly refined in the future based on student feedback! By the end of this course, you will understand the fundamentals of the C Programming Language,OOP Data Structures, and make yourself more marketable for entry level programming positions. You will understand variables and the different data types, be able to utilize functions and arrays, understand the concept of pointers, learn about control flow (decision statements and iteration).You will be in a position to apply for real-time programming positions, and truly understand the core language that most modern languages are based on! C allows you to have a lot of control as to how you use computer resources, so in the right hands its speed and ability to cheaply use resources should be able to surpass other languages.

Nowadays, people prefer using smart and interactive apps instead of basic ones. With continually evolving technologies, it is essential always to stay up-to-date. This means that the apps, games, and gadgets must change and become more dynamic. Are you wondering how all these interactive apps of the future are created? Would you like to know how come the Google Assistant understands what you're saying and can even help you with using your phone more proficiently?

Two people meet, share a mutual attraction, then it all goes belly up. A tale as old as time that can prove as tiring as it is canonical. But it doesn't have to be this way. Am I obsessed with AI's increasing involvement in human love lives? I got carried away with the wine and wrote a speculative thriller about it.

Preview this course - GET COUPON CODE Learn why and where K-Means is a powerful tool Clustering is a very important part of machine learning. Especially unsupervised machine learning is a rising topic in the whole field of artificial intelligence. If we want to learn about cluster analysis, there is no better method to start with, than the k-means algorithm. Unlike other courses, it offers NOT ONLY the guided demonstrations of the R-scripts but also covers theoretical background that will allow you to FULLY UNDERSTAND & APPLY UNSUPERVISED MACHINE LEARNING (K-means) in R. Get a good intuition of the algorithm The K-Means algorithm is explained in detail. We will first cover the principle mechanics without any mathematical formulas, just by visually observing data points and clustering behavior.

Machine learning runs the world. It generates predictions for each individual customer, employee, voter, and suspect, and these predictions drive millions of business decisions more effectively, determining whom to call, mail, approve, test, diagnose, warn, investigate, incarcerate, set up on a date, or medicate. But, to make this work, you've got to bridge what is a prevalent gap between business leadership and technical know-how. Launching machine learning is as much a management endeavor as a technical one. Its success relies on a very particular business leadership practice.

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As the name suggests, it is the part that introduces you to the entire course (which in itself is an introduction to computer science). You can treat this section as "mini-version" of the rest of the course. So it is the part that shows you what kind of topics you may expect in further parts of the course. I cover the various topics very briefly to give you an overall picture of the topic. For example, I mention here very briefly the topic of programming, giving a very general view of it. However, the course has a whole part named "Software", in which I show you exactly what is it about. I explain how programs are created today, what tools are used etc. Probably the completion of this part of the course, therefore, will not take you much time.

We are a group of experts, PhDs and Practitioners of Artificial Intelligence, Computer Science, Machine Learning, and Statistics. Some of us work in big companies like Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. We decided to produce a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of Machine Learning, Statistics, Artificial Intelligence, and Data Science. Initially, our objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory and without a long reading. Today we also publish a more complete course on some topics for a wider audience.

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