How is artificial intelligence changing the world? If you want to understand more about the power and potential of AI and machine learning, a great place to start is with TED Talks. Presented by thought leaders in the field of artificial intelligence, TED Talks give anyone the opportunity to gain insider knowledge from an expert's perspective. We at Gengo have put together a collection of the best AI TED Talks. Check them out for yourself!

Peggy and Dr. Cathy Kapica, founder and CEO, The Awegrin Institute, discuss why food science is important--and how technology factors in. She says 2020 is the next update of the U.S. Dietary Guidelines, and they are the foundation of health nutrition and health messaging. She adds that food is the original medicine, and food does not become nutrition until it is eaten, and that artificial intelligence has helped to bring a more affordable and safe food supply.

Buy the guide with confidence and without fear. This guide was written to help you. If you're not happy, email team@datascienceweekly.org and you'll receive a refund.

Today's classroom isn't just a place for education – it's also a laboratory, and teachers are expected to collect huge amounts of data, with the goal of improving learning outcomes. Despite the best intentions, however, this emphasis on educational data is especially onerous for already overworked teachers, meaning they need better tools to assist with collecting that data. That's where new recording strategies can help. Colleges were among the first to place a heavy emphasis on analytics because of their greater resources and research-driven agendas; and as such, they were the first to realize the value of educational data. For example, facing low graduation rates, colleges examined student records and discovered that students were struggling with English classes, even as they were thriving in other subject areas. Based on that data, colleges were able to address shortfalls in entering students' reading and writing skills and develop programs to enable them to succeed.

I'm a physicist who works at a YC startup. Our job is to help new grads get hired into their first machine learning jobs. Some time ago, I wrote about the things you should do to get hired into your first machine learning job. I said in that post that one thing you should do is build a portfolio of your personal machine learning projects. But I left out the part about how to actually to do that, so in this post, I'll tell you how. If you don't have a track record, personal projects are the closest substitute.)

Although many courses are very mathematical or too practical in nature, this course strikes a careful balance between the two to provide a solid foundation in deep learning for you to explore further if you are interested in research in the field of deep learning and/or applied deep learning. It is purposefully made for anyone without a strong background in mathematics. And for those with a strong background, it would accelerate your learning in understanding the different models in deep learning. This entire course is delivered in a Python Notebook such that you can follow along the videos and replicate the results. You can practice and tweak the models until you truly understand every line of code as we go along.

News Flash! 2019 is here, whether you are ready or not. Almost no one in the education sector is ready for the Future, capital "F", that I learned about when taking an online course on artificial intelligence offered through the Massachusetts Institute of Technology. Which means we need to get cracking. You might be thinking that artificial intelligence (AI) is not something people in education need to focus on too much. After all, AI is really about replacing routine jobs in factories and large businesses, right?

This is a practical introduction to Machine Learning using Python programming language. Machine Learning allows you to create systems and models that understand large amounts of data. These models support our decision making in a range of fields, including market prediction, within scientific research and statistical analysis. This course will teach you how to use statistical techniques and machine learning algorithms that enable a computer system to learn from different types of data. This is a ten week introductory course in Machine Learning using Python, which is a widely used programming language in the field of Machine Learning.

We are pleased to announce a basic introduction to machine learning presentation that provides an overview of the basic algorithms by Donald Woodlock, InterSystems VP of HealthShare Platforms.

Stop by the DENSO booth to see the latest in AI processing solutions from Thinci. We will be showing our Graph Streaming Processor, Autonomous Driving Suite, Plug & Code AI Platform and our latest small form factor M.2 AI accelerator cards.