Hari Thapliyaal

Hari Thapliyal is a vivid blogger on various subjects including Data Science, Project Management, and Advait-Vedanta Philosophy. He has Master’s degrees in Computers, Business Management, Data Science, and Economics. He is pursuing his Doctorate in AI (NLP) from the Swiss School of Business Management (Geneva, Switzerland). Hari has around 3 decades of experience in management & leadership, training, consulting, and coaching in technology. 16+ years in all phases of software product development. 10+ years in course design, training, coaching, and consulting on Project Management. 3+ years experience in course development, exploring, experimenting, training, coaching, and mentoring hundreds of professionals in Data Science, AI, CV, NLP, complex machine learning algorithms, statistical modeling, identifying patterns, and extracting valuable insights. He has diverse experience in planning & executing multiple projects and liaising with key stakeholders to identify & resolve the business problem and deliver excellent results. In his spare time, he loves to Meditate in some secluded place or in nature.

DS, AI, ML Online Course, Tutorial, Videos

DS, AI, ML Online Course, Tutorial, Videos

Courses

  1. Machine Learning – Stanford by Andrew Ng in Coursera (2010-2014)
  2. Machine Learning – Caltech by Yaser Abu-Mostafa (2012-2014)
  3. Machine Learning – Carnegie Mellon by Tom Mitchell (Spring 2011)
  4. Neural Networks for Machine Learning by Geoffrey Hinton in Coursera (2012)
  5. Neural networks class by Hugo Larochelle from Université de Sherbrooke (2013)
  6. Deep Learning Course by CILVR lab @ NYU (2014)
  7. A.I – Berkeley by Dan Klein and Pieter Abbeel (2013)
  8. A.I – MIT by Patrick Henry Winston (2010)
  9. Vision and learning – computers and brains by Shimon Ullman, Tomaso Poggio, Ethan Meyers @ MIT (2013)
  10. Convolutional Neural Networks for Visual Recognition – Stanford by Fei-Fei Li, Andrej Karpathy (2017)
  11. Deep Learning for Natural Language Processing – Stanford
  12. Neural Networks – usherbrooke
  13. Machine Learning – Oxford (2014-2015)
  14. Deep Learning – Nvidia (2015)
  15. Graduate Summer School: Deep Learning, Feature Learning by Geoffrey Hinton, Yoshua Bengio, Yann LeCun, Andrew Ng, Nando de Freitas and several others @ IPAM, UCLA (2012)
  16. Deep Learning – Udacity/Google by Vincent Vanhoucke and Arpan Chakraborty (2016)
  17. Deep Learning – UWaterloo by Prof. Ali Ghodsi at University of Waterloo (2015)
  18. Statistical Machine Learning – CMU by Prof. Larry Wasserman
  19. Deep Learning Course by Yann LeCun (2016)
  20. Designing, Visualizing and Understanding Deep Neural Networks-UC Berkeley
  21. UVA Deep Learning Course MSc in Artificial Intelligence for the University of Amsterdam.
  22. MIT 6.S094: Deep Learning for Self-Driving Cars
  23. MIT 6.S191: Introduction to Deep Learning
  24. Berkeley CS 294: Deep Reinforcement Learning
  25. Keras in Motion video course
  26. Practical Deep Learning For Coders by Jeremy Howard – Fast.ai
  27. Introduction to Deep Learning by Prof. Bhiksha Raj (2017)
  28. AI for Everyone by Andrew Ng (2019)
  29. MIT Intro to Deep Learning 7 day bootcamp – A seven day bootcamp designed in MIT to introduce deep learning methods and applications (2019)
  30. Deep Blueberry: Deep Learning – 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)
  31. Spinning Up in Deep Reinforcement Learning – A free deep reinforcement learning course by OpenAI (2019)
  32. Deep Learning Specialization – Coursera – Breaking into AI with the best course from Andrew NG.
  33. Deep Learning – UC Berkeley STAT-157 by Alex Smola and Mu Li (2019)
  34. Machine Learning for Mere Mortals video course by Nick Chase
  35. Machine Learning Crash Course with TensorFlow APIs -Google AI
  36. Deep Learning from the Foundations Jeremy Howard – Fast.ai
  37. Deep Reinforcement Learning (nanodegree) – Udacity a 3-6 month Udacity nanodegree, spanning multiple courses (2018)
  38. Grokking Deep Learning in Motion by Beau Carnes (2018)
  39. Face Detection with Computer Vision and Deep Learning by Hakan Cebeci
  40. Presentation skills: Designing Presentation Slides - Coursera
  41. Mathematics for Machine Learning: Multivariate Calculus - Coursera
  42. Machine Learning – Home Coursera
  43. Mathematics for Machine Learning: Multivariate Calculus - Coursera
  44. Data Science Certificates - Coursera
  45. Edureka
  46. Edureka-Cloudera Manager
  47. Udemy Courses
  48. Courses – Online Reiki Course
  49. DataCamp Courses
  50. Byju
  51. udacity
  52. What is Spark – A Comparison Between Spark vs. Hadoop
  53. Microsoft Azure Machine Learning Studio (classic)
  54. Welcome to The Apache Software Foundation!
  55. Making India Employable - Vivid Vision 10 10 10
  56. GpI8H5 – Online Python3 Interpreter & Debugging Tool – Ideone.com
  57. Google I/O 2019 – All Sessions – YouTube
  58. TensorFlow at Google I/O 2019 – YouTube
  59. Quantum Mechanics - BSc Lectures by Prof. H C Verma and Team
  60. Open Pathshala - Your Best Source to Learn Sanskrit
  61. Class Central #1 Search Engine for Free Online Courses & MOOCs
  62. Free Online Course: Mathematics for Machine Learning: Multivariate Calculus from Coursera - Class Central
  63. e Learning for Basic Science and Maths
  64. Online Classes by Skillshare - Start for Free Today
  65. Learn online marketing with free courses – Google Digital Garage
  66. Moz Blog – SEO and Inbound Marketing Blog – Moz
  67. NPTEL Online Courses Mobile
  68. Learn Python, Data Viz, Pandas & More - Tutorials - Kaggle
  69. Data Science Training

Tutorials

  1. UFLDL Tutorial 1
  2. UFLDL Tutorial 2
  3. Deep Learning for NLP (without Magic)
  4. A Deep Learning Tutorial: From Perceptrons to Deep Networks
  5. Deep Learning from the Bottom up
  6. Theano Tutorial
  7. Neural Networks for Matlab
  8. Using convolutional neural nets to detect facial keypoints tutorial
  9. Torch7 Tutorials
  10. The Best Machine Learning Tutorials On The Web
  11. VGG Convolutional Neural Networks Practical
  12. TensorFlow tutorials
  13. More TensorFlow tutorials
  14. TensorFlow Python Notebooks
  15. Keras and Lasagne Deep Learning Tutorials
  16. Classification on raw time series in TensorFlow with a LSTM RNN
  17. Using convolutional neural nets to detect facial keypoints tutorial
  18. TensorFlow-World
  19. Deep Learning with Python
  20. Grokking Deep Learning
  21. Deep Learning for Search
  22. Keras Tutorial: Content Based Image Retrieval Using a Convolutional Denoising Autoencoder
  23. Pytorch Tutorial by Yunjey Choi
  24. Understanding deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras
  25. Overview and benchmark of traditional and deep learning models in text classification
  26. Hardware for AI: Understanding computer hardware & build your own computer
  27. Programming Community Curated Resources
  28. The Illustrated Self-Supervised Learning
  29. Visual Paper Summary: ALBERT (A Lite BERT)

Videos and Lectures

  1. How To Create A Mind By Ray Kurzweil
  2. Deep Learning, Self-Taught Learning and Unsupervised Feature Learning By Andrew Ng
  3. Recent Developments in Deep Learning By Geoff Hinton
  4. The Unreasonable Effectiveness of Deep Learning by Yann LeCun
  5. Deep Learning of Representations by Yoshua bengio
  6. Principles of Hierarchical Temporal Memory by Jeff Hawkins
  7. Machine Learning Discussion Group – Deep Learning w/ Stanford AI Lab by Adam Coates
  8. Making Sense of the World with Deep Learning By Adam Coates
  9. Demystifying Unsupervised Feature Learning By Adam Coates
  10. Visual Perception with Deep Learning By Yann LeCun
  11. The Next Generation of Neural Networks By Geoffrey Hinton at GoogleTechTalks
  12. The wonderful and terrifying implications of computers that can learn By Jeremy Howard at TEDxBrussels
  13. Unsupervised Deep Learning – Stanford by Andrew Ng in Stanford (2011)
  14. Natural Language Processing By Chris Manning in Stanford
  15. A beginners Guide to Deep Neural Networks By Natalie Hammel and Lorraine Yurshansky
  16. Deep Learning: Intelligence from Big Data by Steve Jurvetson (and panel) at VLAB in Stanford.
  17. Introduction to Artificial Neural Networks and Deep Learning by Leo Isikdogan at Motorola Mobility HQ
  18. NIPS 2016 lecture and workshop videos – NIPS 2016
  19. Deep Learning Crash Course: a series of mini-lectures by Leo Isikdogan on YouTube (2018)
  20. Deep Learning Crash Course By Oliver Zeigermann
  21. Deep Learning with R in Motion: a live video course that teaches how to apply deep learning to text and images using the powerful Keras library and its R language interface.
  22. 8 Essential Tips for People starting a Career in Data Science.
  23. Cheatsheet: How to become a data scientist.
  24. The Art of Learning Data Science.
  25. The Periodic Table of Data Science.
  26. Aspiring Data Scientists! Start to learn Statistics with these 6 books!
  27. 8 Skills You Need to Be a Data Scientist
  28. Top 10 Essential Books for the Data Enthusiast
  29. Aspiring data scientist? Master these fundamentals.
  30. How to Become a Data Scientist – On your own.

GRETL – Great Statistical software for Beginners

  1. Simple Linear Regression https://lnkd.in/ecfsV9c
  2. Coding Dummy Variables https://lnkd.in/ef7Yd7f
  3. Forecasting New Observations https://lnkd.in/eNKbxbU
  4. Forecasting a Large Number of Observations https://lnkd.in/eHmibGs
  5. Logistic Regression https://lnkd.in/eRfhQ87
  6. Forecasting and Confusion Matrix https://lnkd.in/eaqrFJr
  7. Modeling and Forecasting Time Series Data https://lnkd.in/e6fqKpF
  8. Comparing Time Series Trend Models https://lnkd.in/eKjEUAE
  9. Khan Academy is the best online free resource to learn Math for Data Science. ( https://www.khanacademy.org/math/).
  10. Krista King has also done a great job in creating an exceptionally good introductory course. She is too good at designing the course. ( https://www.udemy.com/user/kristaking/.
  11. 3Blue1Brown ( https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw/playlists).
  12. Every Intro to Data Science Course on the Internet, Ranked. (https://lnkd.in/fQDMiNX )
  13. What would be useful for aspiring data scientists to know? (https://lnkd.in/fmcFyN7)