Create a computer vision program with python and OpenCV.

Introduction to Machine Learning:- What is Machine Learning?,

Note: This course is for candidates having 6 months of working experience in developing RPA solutions. Robotics Process Automation (RPA) is the talk of the town in the business world these days – and with a good reason. RPA is revolutionizing the way we work by removing the boring and repetitive work. This gives the employees time to be creative and do more interesting work. At the front of this revolution is UiPath, which is widely acknowledged as the leading RPA software vendor.

Sometime ago, the world's most affable and recognizable AI leader, Andrew Ng launched a specialization called AI for medicine through his MOOC institution, deeplearning.ai. I have always been a big fan of Andrew Ng, and it was he who had introduced me to the world of machine learning through his grainy Youtube videos of Stanford lectures back in 2012. I was very excited that finally, Andrew Ng has finally turned his attention to the critical shortage of AI experts in the medical field . Truth be told, AI in the medical world has not seen as much progress as other domains like personalized advertisements, recommendations, autonomous driving etc. There are lot of complex issues like data privacy, small sample sizes etc. which I would prefer to discuss in depth in another post.

In this course you will learn all about the mathematical optimization of linear programming for data science and business analytics. This course is very unique and have its own importance in their respective disciplines. The data science and business study heavily rely on optimization. Optimization is the study of analysis and interpreting mathematical data under the special rules and formula. The length of the course is more than 6 hours and there are total more than 4 sections in this course.

Deep reinforcement learning algorithms (Sutton & Barto, 1998) are effective at learning, often from raw sensor inputs, control policies that optimize for a quantitative reward signal. Learning these policies can require experiencing millions of unsafe actions. Even if a safe policy is finally learned - which will happen only if the reward signal reflects all relevant safety priorities - providing a purely statistical guarantee that the optimal policy is safe requires an unrealistic amount of training data (Kalra & Paddock, 2016). The difficulty of establishing the safety of these algorithms makes it difficult to justify the use of reinforcement learning in safety-critical domains where industry standards demand strong evidence of safety prior to deployment (ISO-26262, 2011). Formal verification provides a rigorous way of establishing safety for traditional control systems (Clarke et al., 2018). The problem of providing formal guarantees in RL is called formally constrained reinforcement learning (FCRL).

This course is bundle of two courses of linear algebra and probability and statistics. So, students will learn complete contents of probability and statistics and linear algebra. It is not like that you will not complete all the contents in this 7 hours videos course. This is a beautiful course and I have designed this course according to the need of the students. WHERE THIS COURSE IS APPLICABLE?

The abundance of knowledge and resources can be at times overwhelming specifically when you are talking about new age technologies like Natural Language Processing or what we popularly call it as NLP. When trying to educate yourself, you should always choose resources with solid base and fresh books to impart unprecedented package of learnings. Here is the list of top books that can help you expand your NLP knowledge. One of the most widely referenced and recommended NLP books, written by Stanford University professor Dan Jurafsky and University of Colorado professor James Martin, provides a deep-dive guide on the subject of language processing. It's intended to accompany undergraduate or advanced graduate courses in Natural Language Processing or Computational Linguistics. However, it's a must-read for anyone diving into the theory and application of language processing as they grow and strengthen their analytics capabilities.

Are you ready to start your path to becoming a Machine Learning expert! Are you ready to train your machine like a father trains his son! A breakthrough in Machine Learning would be worth ten Microsofts." -Bill Gates There are lots of courses and lectures out there regarding Support Vector Machine. This course is truly a step-by-step. In every new tutorial we build on what had already learned and move one extra step forward and then we assign you a small task that is solved in the beginning of next video.

If companies were already investing in automation and AI technologies before March 2020, they have only accelerated those investments since. No one expected the jolt the COVID-19 pandemic would bring to business. With leaders looking for ways to avoid human contact, machines, software, and new processes that avoid those humans are even more imperative. That's why we've committed a whole day of our Transform 2020 digital conference to the Technology and Automation Summit, presented by collaborative data science software maker Dataiku, on July 15. Hear from industry leaders at Dataiku, Intuit, Chase, Walmart, Goldman Sachs, and more about their journeys and learnings in implementing these technologies, how they unlocked value/ROI from them, and their thoughts about what the future holds.