Distance Learning


Artificial intelligence genius Andrew Ng has another AI project in the works

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AI promises to transform the world. There, Ng was chief scientist and headed the company's (what else) Artificial Intelligence Group, turning the Beijing-based giant into one of only a handful of companies in the world with expertise in each of the major AI categories: speech, natural language processing, computer vision, machine learning, and knowledge graph. After Baidu, I am excited to continue working toward the AI transformation of our society and the use of AI to make life better for everyone." One thing that excites me is finding ways to support the global AI community so that people everywhere can access the knowledge and tools that they need to make AI transformations."


Andrew Ng to launch Deeplearning.ai months after departure from Baidu

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Former Baidu chief scientist Andrew Ng today announced plans to launch a new business called Deeplearning.ai. Considered one of the top minds in deep learning today, Ng left Baidu in March and was with the company since 2014 following work as cocreator of the Google Brain AI research project. Hope will help many of you: deeplearning.ai


Introduction to Mathematical Thinking Coursera

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School math typically focuses on learning procedures to solve highly stereotyped problems. Professional mathematicians think a certain way to solve real problems, problems that can arise from the everyday world, or from science, or from within mathematics itself. The key to success in school math is to learn to think inside-the-box. In contrast, a key feature of mathematical thinking is thinking outside-the-box – a valuable ability in today's world.


The Best Data Science Courses on the Internet, Ranked by Your Reviews

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We compiled average ratings and number of reviews from Class Central and other review sites to calculate a weighted average rating for each course. Big Data University's Data Science Fundamentals covers the full data science process and introduces Python, R, and several other open-source tools. An effective practical introduction, Kirill Eremenko's Tableau 10 series focuses mostly on tool coverage (Tableau) rather than data visualization theory. Kirill Eremenko and Hadelin de Ponteves' Machine Learning A-Z is an impressively detailed offering that provides instruction in both Python and R, which is rare and can't be said for any of the other top courses.


Conversational Books – Chatbot's Life

#artificialintelligence

The future of engagement, content consumption and content production is being driven by teens. And that's right they are PAYING to read books or short stories via a conversational inference. I am sure that this is just the start of what is possible and this business model is providing inspiration for the team at QuizChatBot.com We are currently working with online course providers, and training providers to turn their online courses into chatbot conversations. Adding this layer of engagement to allow users to consume content by conversation.


A Special Free Preview Of Udacity's Artificial Intelligence Nanodegree Program Udacity

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When it launched, the Udacity Artificial Intelligence Nanodegree program became a kind of landmark in this history of AI. We are very excited to invite you to a very special, very limited, free preview of our Artificial Intelligence Nanodegree program! For the Artificial Intelligence Nanodegree program, we have designed a curriculum that will help you establish your fundamentals and pursue your passions. Please accept our invitation to explore Udacity's Artificial Intelligence Nanodegree program.


Top Machine Learning MOOCs and Online Lectures: A Comprehensive Survey

@machinelearnbot

That said, Ng's course skips a lot of high level machine learning problems and algorithms. I found this course on Youtube by another excellent Machine Learning researcher Nando de Freitas. So, you see Math, ML, AI, Neural Networks Deep Learning; everything possible has been covered in this high level course. But, if you want to see the level of difficulty of advanced machine learning and neural networks' problems and what to do next this is a good starting point.


Wouldn't You Like Alexa Better if It Knew When It Was Annoying You?

IEEE Spectrum Robotics Channel

Speaking at the Computer History Museum last week, el Kaliouby said that she has been working to teach computers to read human faces since 2000 as a PhD student at Cambridge University. Since then, she's been using machine learning, and more recently deep learning, to teach computers to read faces, spinning Affectiva out of the MIT Media Lab in 2009 to commercialize her work. She still thinks emotional intelligence technology--or EI--will be a huge boon to this community, potentially providing a sort of emotional hearing aid. She sees smart phones with EI as potentially able to regularly check a person's mental state, providing early warning of depression, anxiety, or other problems.


Cluster Analysis and Unsupervised Machine Learning in Python

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Cluster analysis is a staple of unsupervised machine learning and data science. Do you ever wonder how we get the data that we use in our supervised machine learning algorithms? Next, because in machine learning we like to talk about probability distributions, we'll go into Gaussian mixture models and kernel density estimation, where we talk about how to "learn" the probability distribution of a set of data. All the algorithms we'll talk about in this course are staples in machine learning and data science, so if you want to know how to automatically find patterns in your data with data mining and pattern extraction, without needing someone to put in manual work to label that data, then this course is for you.


Artificial Intelligence: Reinforcement Learning in Python

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These tasks are pretty trivial compared to what we think of AIs doing - playing chess and Go, driving cars, and beating video games at a superhuman level. We saw AIs playing video games like Doom and Super Mario. Learning about supervised and unsupervised machine learning is no small feat. If you're ready to take on a brand new challenge, and learn about AI techniques that you've never seen before in traditional supervised machine learning, unsupervised machine learning, or even deep learning, then this course is for you.