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Originally published at LinkedIn Pulse. Early last month, I presented a half-day tutorial on at this year's virtual CVPR 2020. This is a very unique experience, and I would like to share some of the highlights of the tutorial. The tutorial focused on a critical problem that arises as AI moves from experimentation to production; that is, how to seamlessly scale AI to distributed Big Data. Today, AI researchers and data scientists need to go through a mountain of pains to apply AI models to production dataset that is stored in distributed Big Data cluster.

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Experts from China and abroad shared their ideas on how artificial intelligence can empower education at an online forum during the World Artificial Intelligence Conference on Friday. It attracted some 1 million viewers. Wang Ping, director of the Shanghai Education Commission, shared Shanghai's experience in organizing the largest-ever online education program during the COVID-19 pandemic at the forum venue, the Shanghai Education TV Station. He said Shanghai has been building infrastructure and developing teachers' capability in using modern technology. "More than 3 million teachers and students from Shanghai schools have taught or learnt at home," he said. "It was a test of Shanghai's information development and a precursor to the future online education featuring AI technology."

You got intrigued by the machine learning world and wanted to get started as soon as possible, read all the articles, watched all the videos, but still isn't sure about where to start, welcome to the club. Before we dive into the machine learning world, you should take a step back and think, what is stopping you from getting started? If you think about it, most of the time, we presuppose things about ourselves and assume that to be true without question. The most normal presumption that we make about ourselves is that we need to have prior knowledge before getting started. Get a degree, complete a course, or have a good understanding of a particular subject.

A perfect course for Bachelors / Masters / PhD students who are getting started into Drug Discovery research. This course is specially designed keeping in view of beginner level knowledge on Artificial Intelligence, Machine learning and computational drug discovery applications for science students. By the end of this course participants will be equipped with the basic knowledge required to navigate their drug discovery project making use of the Artificial Intelligence and Machine learning based tools.Who this course is for:

In this machine learning tutorial you will learn about machine learning algorithms using various analogies related to real life. Understand the concepts of Supervised, Unsupervised and Reinforcement Learning and learn how to write a code for machine learning using python.

K-Nearest Neighbors (KNN) Algoritm in Machine Learning will help you to master all the concepts of KNN. KNN algorithm is one of the simplest, non-parametric, lazy classification learning algorithm. Its purpose is to use a dataset in which the data points are separated into several classes to predict the classification of a new sample point. This tutorial on "KNN Algoritm in Machine Learning" will help you to master all the concepts of K-nearest neighbors. Its purpose is to use a dataset in which the data points are separated into several classes to predict the classification of a new sample point.

The Deep Learning Training at IT Guru will provide you the best knowledge on deep learning fundamentals, neural networks, natural language processing, etc with live experts. Learning Online Deep learning makes you a master in this subject that includes building blocks, implementing neural networks, programming languages & tools, etc. Our best Deep learning Course module will provide you a way to become certified in Deep learning. So, join hands with ITGuru for accepting new challenges and make the best solutions through Advanced Deep learning. The Online Deep learning Training basics and other features will make you an expert in the Deep learning algorithms, etc to deal with real-time tasks.

The Covid-19 pandemic has hit the global economy hard and has severely affected small and medium companies. As a result, the unemployment rate has plunged rapidly. However, on a positive note, the saying'a crisis often paves way for new opportunities' holds true. The coming days will see a boom in data science and artificial intelligence jobs. There is an unprecedented demand for latest technologies like artificial intelligence (AI) and machine learning (ML) that could be used for accurate and real time prediction of vulnerable population at greater risk of infection along with precise identification of high-risk zones.