In this python machine learning course, learn both supervised and unsupervised learning in python from scratch. Enroll in this course and boost your career now In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By becoming proficient in unsupervised & supervised learning in Python, you can give your company a competitive edge - and boost your career to the next level.

Become an AI & Machine Learning Professional with this lightning deal by Eduonix. Limited time offer, Hurry Up! AI and Machine Learning for Professionals A complete guide to master machine learning concepts and create real world ML solutions Instructors: Eduonix Learning Solutions, Manuj Aggarwal Why This Deal Be an advance Artificial Intelligence practitioner with our unique course bundle which covers courses for students at all stages of learning. A complete guide to master machine learning concepts and create real world ML solutions. Starting at the very beginning, this course will help you breakdown machine learning into simple and easy to understand concepts. The course covers a variety of different machine learning concepts such as supervised learning, unsupervised learning, reinforced learning and even neural networks.

Did you know that every time you upload a photo to Facebook, the platform uses facial recognition algorithms to identify the people in that image? Or that certain governments around the world use face recognition technology to identify and catch criminals? I don't need to tell you that you can now unlock smartphones with your face! The applications of this sub-domain of computer vision are vast and businesses around the world are already reaping the benefits. The usage of face recognition models is only going to increase in the next few years so why not teach yourself how to build one from scratch?

Some users love it while others hate it. Some experts estimate that Windows 10 dominates nearly 40% of the desktop OS market, handily surpassing the popularity of Windows 7. Speaking of, are you still using Windows 7? Microsoft is ending support for the 10-year-old operating system in January. Tap or click to learn how to bring your PC up to date before it's too late. Using the slogan "upgrade your world," Microsoft has described Windows 10 as the "final" version. Instead of replacing the operating system every few years, Windows 10 users have been able to download free updates.

As a Christmas present to the world, Finland is making its online crash course in artificial intelligence available to everyone for free. The Nordic nation launched the 6-week "Elements of AI" course last year as a means of educating their citizens on the revolutionary new technology. Since Finland will be passing on its rotating EU presidency to another member state at the end of the year, the country decided to graciously celebrate the occasion by translating the course materials into English, Swedish, Estonian, and German--as well as Finnish--and making it available for EU citizens to take (although there are no geographical limitations on who can take the course). The course, which has thus far been taken by more than 220,000 students from about 110 countries, has become the most popular course offered by the University of Helsinki. It consists of seven modules, each of which takes about 5 to 10 hours to complete.

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In 2016, in a face-to-face talk, I had advised The University of the West Indies (UWI) Mona's artificial intelligence lecturer to introduce artificial neural networks, also known as modern artificial intelligence (AI), as an independent course to the computer science degree. Artificial neural networks power many smart applications today, ranging from self-driving cars to automated disease diagnosers. In 2016, I also began something called Machine Learning Jamaica Institute, which later, on June 2, 2018, had a free online curriculum, including a 2017 artificial intelligence book written by myself. The goal was to establish a physical building dedicated to artificial intelligence, to prepare the nation for growing automation. Of note, this year Abu Dhabi, capital of the United Arab Emirates, announced it would start "the world's first University of Artificial Intelligence", capitalising on the fact that an increasing number of countries are becoming more and more serious about artificial intelligence education.

Classification is a predictive modeling problem that involves predicting a class label for a given example. It is generally assumed that the distribution of examples in the training dataset is even across all of the classes. In practice, this is rarely the case. Those classification predictive models where the distribution of examples across class labels is not equal (e.g. are skewed) are called "imbalanced classification." Typically, a slight imbalance is not a problem and standard machine learning techniques can be used. In those cases where the imbalance is severe, such as a 1:100, 1:1000, or higher ratio of the minority to the majority class, then specialized techniques are required.

The ground breaking advancements in Artificial Intelligence (AI) is creating tremendous opportunities for transforming industries and virtually every aspect of our existence. The demand for people well versed with AI skill-set is exploding and it is expected to generate over 50 million new jobs in the coming years. There are thousands of educational materials out there for learning Artificial Intelligence (AI). However, much of AI Tutorials and Courses are without Graded Assignments or Peer Feedback and have a poor quality. So, I decided to inspire your AI journey by compiling the best courses from the world-class educators, so that you can learn to create AI powered applications that can give you an edge in becoming a skilled AI -- Engineer/ Scientist/ Researcher/ Practitioner.

This is the SECOND in a series of posts on applying Tim Ferriss' accelerated learning framework to Data Science. My goal is to become a world-class (top 5%) Data Scientist in 6 months, while open-sourcing everything I find & learn on the way. And if you stick around until the end, you're in for a special treat. A simple Google search of "how to learn Data Science" returns thousands of learning plans, degree programs, tutorials, and bootcamps. It's never been more difficult for a beginner to find signal in the noise. Everyone seems to have a different opinion, and the only common approach appears to be dumping a long list of courses to take and books to read, all the while providing little to no context into how these concepts fit into the bigger picture. This post is my attempt to convert all the buzzwords & fluffy terminology into explicitly-learnable skills.