Machine Learning

March 9, 2017
Introduction Machine Learning is tricky. No matter how many books you read, tutorials you finish or problems you solve, there will always be a data set you might come across where you get clueless. Specially, when you are in your early days of Machine Learning. Isn't it ? In this blog post, you'll learn some […]
March 7, 2017
Introduction Deep Learning algorithm is one of the most powerful learning algorithms of the digital era. It has found a unique place in various industrial applications such as fraud detection in credit approval, automated bank loan approval, stock price prediction etc. Some of the more recent uses of neural networks are image recognition and speech recognition. In fact, you'd be amazed […]
March 7, 2017
Introduction Gradient Descent Algorithm is an iterative algorithm to find a Global Minimum of an objective function (cost  function) J(Ө). The categorization of GD algorithm is for accuracy and time consuming factors that are discussed below in detail. This algorithm is widely used in machine learning for minimization of functions. Here,the algorithm to achieve objective goal […]
March 6, 2017
Introduction "This hot new field promises to revolutionize industries from business to government, health care to academia," says the New York Times. People have woken up to the fact that without analyzing the massive amounts of data that’s at their disposal and extracting valuable insights, there really is no way to successfully sustain in the […]
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 […]