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TensorFlow 101: Introduction to Deep Learning - Udemy

@machinelearnbot

Serengil received his MSc in Computer Science from Galatasaray University in 2011. He has been working as a software developer for a fintech company since 2010. Currently, he is a member of AI and Machine Learning team as a Data Scientist. His current research interests are Machine Learning and Cryptography. He has published several research papers about these motivations.


Learning Path:TensorFlow: The Road to TensorFlow-2nd Edition

@machinelearnbot

Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. It can be hard to get started with machine learning, particularly as new frameworks like TensorFlow start to gain traction across enterprise companies. TensorFlow is an open source software library for numerical computation using data flow graphs. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. This Learning Path begins by covering a mastery on Python with a deep focus on unlocking Python's secrets.


Learning Path: From Python Programming to Data Science

@machinelearnbot

Python has become the language of choice for most data analysts/data scientists to perform various tasks of data science. If you're looking forward to implementing Python in your data science projects to enhance data discovery, then this is the perfect Learning Path is for you. Starting out at the basic level, this Learning Path will take you through all the stages of data science in a step-by-step manner. Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. We begin this journey with nailing down the fundamentals of Python.


AI pioneer Andrew Ng says his new online course will help build 'an AI-powered society'

#artificialintelligence

Lots of people will tell you they're nervous about the changes artificial intelligence will bring to the world, but Andrew Ng is confident it's all for the best. And to bring about that future, Ng, now an adjunct professor at Stanford, will share what he knows best by teaching. Today, Ng is launching a new course on deep learning on Coursera, the online education site he co-founded. The syllabus will follow his popular machine learning course, which has attracted some 2 million enrollments since its launch in 2011. "There's a lot of PR and buzz focused on AI transforming large tech companies, but there's a lot of work that still needs to be done for AI to transform the non-tech companies," Ng tells The Verge.


Andrew Ng's Next Project Takes Aim at the Deep Learning Skills Gap

WIRED

Andrew Ng is a soft-spoken AI researcher whose online postings talk loudly. A March blog post in which the Stanford professor announced he was leaving Chinese search engine Baidu temporarily wiped more than a billion dollars off the company's value. A June tweet about a new Ng website, Deeplearning.ai, Today that speculation is over. Deeplearning.ai is home to a series of online courses Ng says will help spread the benefits of recent advances in machine learning far beyond big tech companies such as Google and Baidu.


Resources to get up to speed in NLP • r/LanguageTechnology

@machinelearnbot

I'm a software engineer with 10 years of experience who recently decided to switch my focus to machine learning. I did the coursera course and did CS231n: Convolutional Neural Networks for Visual Recognition, read up on basic theory, did some image processing networks like VGG, Resnets and most recently trying to get Faster-RCNN to work, so my currently knowledge is ML basics and heavily focussed on ML in the Image domain. I recently landed my first ML job at a company that does mostly NLP, so I lack a lot of knowledge in that domain. I'm currently reading the NLTK book, which has been very approachable in introducing basic concepts in a code-focussed way. So I was wondering if anyone could point me to some good mid to advanced level resources (online courses/videos/books) to get up to speed with where the field is at now, to help me understand current research and more advanced concepts?


Deep Learning Nanodegree Foundation Udacity

#artificialintelligence

"Nanodegree" is a registered trademark of Udacity. Udacity is not an accredited university and we don't confer traditional degrees. Udacity Nanodegree programs represent collaborations with our industry partners who help us develop our content and who hire many of our program graduates.


ZuzooVn/machine-learning-for-software-engineers

#artificialintelligence

Some videos are available only by enrolling in a Coursera or EdX class. It is free to do so, but sometimes the classes are no longer in session so you have to wait a couple of months, so you have no access. I'm going to be adding more videos from public sources and replacing the online course videos over time. I like using university lectures.


ZuzooVn/machine-learning-for-software-engineers

#artificialintelligence

Some videos are available only by enrolling in a Coursera or EdX class. It is free to do so, but sometimes the classes are no longer in session so you have to wait a couple of months, so you have no access. I'm going to be adding more videos from public sources and replacing the online course videos over time. I like using university lectures.