Machine Learning

February 21, 2017
Introduction Data classification is a very important task in machine learning. Support Vector Machines (SVMs) are widely applied in the field of pattern classifications and nonlinear regressions. The original form of the SVM algorithm was introduced by Vladimir N. Vapnik and Alexey Ya. Chervonenkis in 1963. Since then, SVMs have been transformed tremendously to be used […]
Webinar Date: March 9, 2017
HackerEarth is pleased to announce its next webinar on IBM Watson, to help you learn from the best programmers and domain experts from all over the world. Agenda of this webinar: 1. A Technical introduction to Watson Discovery Service 2. How the Watson Discovery Service help find insights from unstructured data? 3. How to add […]
February 20, 2017
Introduction We certainly have some interesting times to look forward to. All ed tech and career forecasts for this decade talk about artificial intelligence (AI) technologies, including machine learning, deep learning, and natural language processing, enabling digital transformation in ways that are quite “out there.” To stay relevant in this economy, the brightest minds, naturally, […]
Webinar Date: March 5, 2017
HackerEarth is pleased to announce its next webinar to help you understand what it really takes to win machine learning competitions. Agenda of this webinar will include: - How Marios started his journey? - Why most people fail to win ? - Useful Machine Learning Strategies for Competitions - Questions! Speaker: Marios Michailidis is Manager […]
February 6, 2017
Introduction Getting learners to read textbooks and use other teaching aids effectively can be tricky. Especially, when the books are just too dreary. In this post, we’ve compiled great e-resources for you digital natives looking to explore the exciting world of Machine Learning and Neural Networks. But before you dive into the deep end, you […]
February 2, 2017
Naive Bayes is a machine learning algorithm for classification problems. It is based on Bayes’ probability theorem. It is primarily used for text classification which involves high dimensional training data sets. A few examples are spam filtration, sentimental analysis, and classifying news articles. It is not only known for its simplicity, but also for its […]
Webinar Date: February 27, 2017
HackerEarth is pleased to announce its next webinar to help you understand on Machine Learning work. About the Session: Ever felt overwhelmed by the plethora of machine learning and data science information? Not sure which algorithms to use to scope out your problem? Matthew Kirk can help you get started. He’s the author of Thoughtful […]
January 30, 2017
Introduction Deep Learning isn't a recent discovery. The seeds were sown back in the 1950s when the first artificial neural network was created. Since then, progress has been rapid, with the structure of the neuron being "re-invented" artificially. Computers and mobiles have now become powerful enough to identify objects from images. Not just images, they can […]
Webinar Date: February 12, 2017
HackerEarth is pleased to announce its next webinar to help you understand what it really takes to become a data scientist. Agenda of this webinar will include answers to these questions: - Why is it the best time to take up Data Science as a career? - How can you take the first step in […]
January 21, 2017
"Data Scientist: Sexiest Job of the 21st century"- Harvard Business Review, 2012 Talking of more recent times, Glassdoor also named it the "best job of the year" for 2016. Where did the title "Data Scientist" come from? It has been there in the market for less than a decade. It was coined by Dr. Dhanurjay Patil, […]