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http://codeinpython.com/tutorials/deep-learning-tensorflow-keras-pytorch/?nonamp=1 Deep Learning #Tensorflow vs #Keras vs #PyTorch #Deep_learning is the application of artificial #neural_networks (ANNs) to learn tasks. These tasks contain more than one hidden layer. Deep learning is part of a broader family of #machine_learning. Machine learning itself is a part of #Artificial_Intelligence(#AI).

https://www.analyticsvidhya.com/learning-paths-data-science-business-analytics-business-intelligence-big-data/learning-path-data-science-python/ Comprehensive learning path – #Data_Science in Python Journey from a Python noob to a Kaggler on Python So, you want to become a data scientist or may be you are already one and want to expand your tool repository. You have landed at the right place. The aim of this page is to provide a comprehensive learning path to people new to python for data analysis. This path provides a comprehensive overview of steps you need to learn to use Python for #data_analysis. If you already have some background, or don’t need all the components, feel free to adapt your own paths and let us know how you made changes in the path. You can also check the mini version of this learning path #Deep_Learning

http://www.kdnuggets.com/2017/09/essential-data-science-machine-learning-deep-learning-cheat-sheets.html#.WdGzWthHcEo.linkedin 30 Essential #Data_Science , #machine_learning & #Deep_Learning Cheat Sheets

https://www.udemy.com/machinelearning/learn/v4/content #machine_learning A-Z™: Hands-On #Python & R In #Data_Science

https://www.kaggle.com/ The Home of #Data_Science & #Machine_Learning Kaggle helps you learn, work, and play

http://www.aparat.com/v/0scM5 Irene Chen A Beginner's Guide to Deep Learning. What is #Deep_Learning ? It has recently exploded in popularity as a complex and incredibly powerful tool. This talk will present the basic concepts underlying deep learning in understandable pieces for complete beginners to #machine_learning.

http://www.aparat.com/v/Corus Advanced users #Deep_Learning, anyone who has followed #machine_learning over the past years has heard it. In this talk I will go past the hype and show what deep learning actually means and how one goes about solving complex machine learning task with a minimum amount of code, with the help of theano, an amazing python library for deep learning.

http://mdp.cdm.depaul.edu/DePy2016 3rd Annual #Conference on #Python applications in #Data_Analysis, #Machine_Learning, and Web May 6, 7 DePaul University - Room LL105 14 E Jackson Blvd Chicago IL 60604, USA

https://magenta.tensorflow.org/welcome-to-magenta We’re happy to announce #Magenta, a project from the Google Brain team that asks: Can we use #machine_learning to create compelling art and music? If so, how? If not, why not? We’ll use #TensorFlow, and we’ll release our models and tools in open source on our GitHub. We’ll also post demos, tutorial blog postings and technical papers. Soon we’ll begin accepting code contributions from the community at large. If you’d like to keep up on Magenta as it grows, you can follow us on our GitHub and join our discussion group.

https://github.com/scikit-learn/scikit-learn #scikit_learn is a Python module for #machine_learning built on top of #SciPy and distributed under the 3-Clause BSD license. The project was started in 2007 by David Cournapeau as a #Google Summer of Code project, and since then many volunteers have contributed. See the AUTHORS.rst file for a complete list of contributors.