Merge branch 'master' into master

README.md

@@ -40,6 +40,7 @@
 7.  [Artificial Intelligence: A Modern Approach](http://aima.cs.berkeley.edu/)
 8.  [Deep Learning in Neural Networks: An Overview](http://arxiv.org/pdf/1404.7828v4.pdf)
 9.  [Artificial intelligence and machine learning: Topic wise explanation](https://leonardoaraujosantos.gitbooks.io/artificial-inteligence/)
+10. [Dive into Deep Learning](https://d2l.ai/) - numpy based interactive Deep Learning book
  
 ### Courses
 
@@ -75,6 +76,7 @@
 29. [Deep Blueberry: Deep Learning](https://mithi.github.io/deep-blueberry) - A free five-weekend plan to self-learners to learn the basics of deep-learning architectures like CNNs, LSTMs, RNNs, VAEs, GANs, DQN, A3C and more (2019)
 30. [Spinning Up in Deep Reinforcement Learning](https://spinningup.openai.com/) - A free deep reinforcement learning course by OpenAI (2019)
 31. [Deep Learning Specialization - Coursera](https://www.coursera.org/specializations/deep-learning) - Breaking into AI with the best course from Andrew NG.
+32. [Deep Learning - UC Berkeley | STAT-157](https://www.youtube.com/playlist?list=PLZSO_6-bSqHQHBCoGaObUljoXAyyqhpFW) by Alex Smola and Mu Li (2019)
 
 ### Videos and Lectures
 
@@ -375,7 +377,7 @@
 73. [NIST Fingerprint and handwriting](ftp://sequoyah.ncsl.nist.gov/pub/databases/data) - datasets - thousands of images (Formats: unknown)
 74. [NIST Fingerprint data](ftp://ftp.cs.columbia.edu/jpeg/other/uuencoded) - compressed multipart uuencoded tar file 
 75. [NLM HyperDoc Visible Human Project](http://www.nlm.nih.gov/research/visible/visible_human.html) - Color, CAT and MRI image samples - over 30 images (Formats: jpeg)
-76. [National Design Repository](http://www.designrepository.org) - Over 55,000 3D CAD and solid models of (mostly) mechanical/machined engineerign designs. (Formats: gif,vrml,wrl,stp,sat) 
+76. [National Design Repository](http://www.designrepository.org) - Over 55,000 3D CAD and solid models of (mostly) mechanical/machined engineering designs. (Formats: gif,vrml,wrl,stp,sat) 
 77. [Geometric & Intelligent Computing Laboratory](http://gicl.mcs.drexel.edu) 
 79. [OSU (MSU) 3D Object Model Database](http://eewww.eng.ohio-state.edu/~flynn/3DDB/Models/) - several sets of 3D object models collected over several years to use in object recognition research (Formats: homebrew, vrml)
 80. [OSU (MSU/WSU) Range Image Database](http://eewww.eng.ohio-state.edu/~flynn/3DDB/RID/) - Hundreds of real and synthetic images (Formats: gif, homebrew)
@@ -478,7 +480,7 @@
 29.  [Tensorflow - Open source software library for numerical computation using data flow graphs](https://github.com/tensorflow/tensorflow)
 30.  [DMTK - Microsoft Distributed Machine Learning Tookit](https://github.com/Microsoft/DMTK)
 31.  [Scikit Flow - Simplified interface for TensorFlow (mimicking Scikit Learn)](https://github.com/google/skflow)
-32.  [MXnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning framework](https://github.com/dmlc/mxnet/)
+32.  [MXnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning framework](https://github.com/apache/incubator-mxnet)
 33.  [Veles - Samsung Distributed machine learning platform](https://github.com/Samsung/veles)
 34.  [Marvin - A Minimalist GPU-only N-Dimensional ConvNets Framework](https://github.com/PrincetonVision/marvin)
 35.  [Apache SINGA - A General Distributed Deep Learning Platform](http://singa.incubator.apache.org/)
@@ -499,6 +501,7 @@
 50.  [TensorForce - A TensorFlow library for applied reinforcement learning](https://github.com/reinforceio/tensorforce)
 51.  [Coach - Reinforcement Learning Coach by Intel® AI Lab](https://github.com/NervanaSystems/coach)
 52.  [albumentations - A fast and framework agnostic image augmentation library](https://github.com/albu/albumentations)
+53.  [garage - A toolkit for reproducible reinforcement learning research](https://github.com/rlworkgroup/garage)
 
 ### Tools
 
@@ -506,6 +509,8 @@
 2.  [Jupyter Notebook](http://jupyter.org) - Web-based notebook environment for interactive computing
 3.  [TensorBoard](https://github.com/tensorflow/tensorboard) - TensorFlow's Visualization Toolkit
 4.  [Visual Studio Tools for AI](https://visualstudio.microsoft.com/downloads/ai-tools-vs) - Develop, debug and deploy deep learning and AI solutions
+5.  [dowel](https://github.com/rlworkgroup/dowel) - A little logger for machine learning research. Log any object to the console, CSVs, TensorBoard, text log files, and more with just one call to `logger.log()`
+6.  [Neptune](https://neptune.ml/) - Lightweight tool for experiment tracking and results visualization. 
 
 ### Miscellaneous