video


9 Best YouTube Playlists and Videos -- Python for Machine Learning

#artificialintelligence

YouTube is a great place to learn about Python for machine learning. Below are the best YouTube playlists for Python that I have accumulated over months of learning. To ensure retention in what you learn, I suggest you watch the videos and make notes, either on paper or Google Docs. This way, you can remember what you learn. Not only that, it is a good practice to write code along with the videos, and write it after chunks and not follow in real-time.


The future of video streaming - Training AI to see with the human eye - Techerati

#artificialintelligence

The latest research from Cisco says that global internet traffic will reach 4.8 zetabytes a year in 2022, or 150,700 gigabytes a second. That research was published before the current coronavirus pandemic, which may well have a dramatic change in the shape and per-type breakdown of global internet traffic as face-to-face meetings are being overwhelmingly replaced with video conference calls and live video streaming. For example, NAB, the biggest event of the year in media production and distribution, has recently announced it will switch to a virtual conference for the 2020 year, with live presentations and meetings taking place via video streamed over the web. We are all aware of the bandwidth issues and contention that can pose a risk for internet connections. This is particularly true for video transfer over IP because of its need for sustained and consistent data rates and for low-latency packet delivery.


How artificial Intelligence is changing insurance

#artificialintelligence

Insurance is an industry that thrives on predictability. The more certain the outcome, the more insurance firms can be sure to offer fair rates and generate value for customers and shareholders alike. As such, it's an industry that has been slow to adopt new technologies and adapt to global change. Today, however, change is here, and more is on the way. Global megatrends, from the imminent arrival of the self-driving car to accelerating climate change, threaten to disrupt the insurance sector in a way that's never been seen before.


Self-supervised learning is the future of AI

#artificialintelligence

Despite the huge contributions of deep learning to the field of artificial intelligence, there's something very wrong with it: It requires huge amounts of data. This is one thing that both the pioneers and critics of deep learning agree on. In fact, deep learning didn't emerge as the leading AI technique until a few years ago because of the limited availability of useful data and the shortage of computing power to process that data. Reducing the data-dependency of deep learning is currently among the top priorities of AI researchers. In his keynote speech at the AAAI conference, computer scientist Yann LeCun discussed the limits of current deep learning techniques and presented the blueprint for "self-supervised learning," his roadmap to solve deep learning's data problem.


Machine Learning in Python: Principal Component Analysis (PCA) for Handling High-Dimensional Data

#artificialintelligence

Machine Learning in Python: Principal Component Analysis (PCA) for Handling High-Dimensional Data In this video, I will be showing you how to perform principal component analysis (PCA) in Python using the scikit-learn package. PCA represents a powerful learning approach that enables the analysis of high-dimensional data as well as reveal the contribution of descriptors in governing the distribution of data clusters. Particularly, we will be creating PCA scree plot, scores plot and loadings plot. This video is part of the [Python Data Science Project] series. If you're new here, it would mean the world to me if you would consider subscribing to this channel.


Drones and self-driving robots used to fight coronavirus in China

#artificialintelligence

China is deploying robots and drones to remotely disinfect hospitals, deliver food and enforce quarantine restrictions as part of the effort to fight coronavirus. Chinese state media has reported that drones and robots are being used by the government to cut the risk of person-to-person transmission of the disease. There are 780 million people that are on some form of residential lockdown in China. Wuhan, the city where the viral outbreak began, has been sealed off from the outside world for weeks. The global death toll from coronavirus topped 2,100 people this week, with over 74,000 infected.


9 Best Machine Learning Courses 2020 • Benzinga

#artificialintelligence

Enroll now in one of Udemy's machine learning courses ranging from beginner to advanced courses taught by industry experts. Are you intrigued by the idea of machine learning? Maybe you've applied core concepts in the workplace and want to take your artificial intelligence expertise to a higher level. An online machine learning course can equip you with the tools needed to understand the basics or accelerate your career. Take a quick look at Benzinga's top picks: Keep the following considerations in mind as you explore machine learning course options and choose the right one for you.


Video: NVIDIA to Accelerate the HPC-AI Convergence - insideHPC

#artificialintelligence

NVIDIA has early identified the promising HPC – AI convergence trend and has been working on enabling it. The growing adoption of NVIDIA Volta GPU by the Top 500 Supercomputers highlights the need of computing acceleration for this HPC & AI convergence. Many projects today demonstrate the benefit of AI for HPC, in terms of accuracy and time to solution, in many domains such as Computational Mechanics (Computational Fluid Mechanics, Solid Mechanics…), Earth Sciences (Climate, Weather and Ocean Modeling), Life Sciences (Genomics, Proteomics…), Computational Chemistry (Quantum Chemistry, Molecular Dynamics…), Computational Physics. NVIDIA today for instance, uses Physics Informed Neural Networks for the heat sink design in our DGX system.



Machine Learning in Python: Building a Linear Regression Model

#artificialintelligence

Machine Learning in Python: Building a Linear Regression Model In this video, I will be showing you how to build a linear regression model in Python using the scikit-learn package. We will be using the Diabetes dataset (built-in data from scikit-learn) and the Boston Housing (download from GitHub) dataset. This video is part of the [Python Data Science Project] series. If you're new here, it would mean the world to me if you would consider subscribing to this channel. Disclaimer: Chanin is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to http://www.amazon.com.