Jan 28
Resources: Reinforcement Learning and Deep Reinforcement Learning
Platform:
Code Examples:
https://becominghuman.ai/reinforcement-learning-with-fifa-and-keras-85ec792e25b2
https://github.com/openai/gym/blob/master/gym/envs/toy_text/nchain.py
Theory
https://arxiv.org/pdf/1712.01815.pdf
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Jan 28
Reinforcement Learning and Deep Learning
An interactive notebook training Keras to play Catch
https://github.com/JannesKlaas/sometimes_deep_sometimes_learning/blob/master/reinforcement.ipynb
Key Papers in Deep RL
https://spinningup.openai.com/en/latest/spinningup/keypapers.html#key-papers-in-deep-rl
DEEP REINFORCEMENT LEARNING
https://arxiv.org/pdf/1810.06339v1.pdf
Tesla: Deep Learning
https://quantdare.com/deep-reinforcement-trading/
Playing Atari with Deep Reinforcement Learning
https://arxiv.org/pdf/1312.5602.pdf
AlphaGo is the first computer program to defeat a professional human Go player, the first to defeat a Go world champion, and is arguably the strongest Go player in history.
https://deepmind.com/research/case-studies/alphago-the-story-so-far
Using Deep Q-Learning in FIFA 18 to perfect the art of free-kicks
https://becominghuman.ai/reinforcement-learning-with-fifa-and-keras-85ec792e25b2
A saturation-balancing control method for enhancing dynamic vehicle stability
https://cecas.clemson.edu/ayalew/Papers/Vehicle%20Systems%20Dynamics%20and%20Control/Papers/A%20Saturation%20Balancing%20Control%20Method%20for%20Enhancing%20Dynamic%20Vehicle%20Stability/IJVD%2061_1-4_Paper%203.pdf
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://arxiv.org/pdf/1712.01815.pdf
Reinforcement Learning Demystified: Solving MDPs with Dynamic Programming
This game presents moves along a linear chain of states, with two actions:
https://github.com/openai/gym/blob/master/gym/envs/toy_text/nchain.py
The Artificial Intelligence Wiki
Glossary:
https://wiki.pathmind.com/glossary
Train DDPG Agent to Control Flying Robot
https://www.mathworks.com/help///deeplearning/ug/train-ddpg-agent-to-control-flying-robot.html
Why should I choose matlab deep learning toolbox over other opensource frameworks like caffe, onnx, pytorch, torch etc?
MnasNet: Platform-Aware Neural Architecture Search for Mobile
https://github.com/tensorflow/tpu/tree/master/models/official/mnasnet
A visual debugger for Jupyter
Debugger: Jupyter
https://blog.jupyter.org/a-visual-debugger-for-jupyter-914e61716559
IPython: https://chrieke.medium.com/jupyter-tips-and-tricks-994fdddb2057
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Jan 27
Health Status: Transport Accident Mortality (M) 2017 and 2015 . Compare countries including Canada and Canadian Provinces
The author is: Sayed AhmednHealth Status: Transport Accident Mortality (M) 2017 and 2015 . [Compare countries including Canada and Canadian Provinces] Dataset: from CIHI, Canada. The same information plotted with different charts. Data files are also attached. If you see any mistakes, or if you need more information, feel free to inform us [‘Measurement units used: Age-standardized rate per 100,000 males. Heatmap might show relative comparisons; not absolute values. The primary goal of these visualizations are to compare. If units are not provided, interpret them as relative values’] These are outputs from a small Python based tool developed on 2019. The tool can generate many more of such plots easily, and will work with data for other purposeSayed Ahmed Linkedin: https://ca.linkedin.com/in/sayedjustetc Blog: http://sitestree.com, http://bangla.salearningschool.com 
csv_data_file_for_2017_for indicator_Transport_Accident_Mortality_(M)_for_plot_heatmap_across_indicators csv_data_file_for_2017_for indicator_Transport_Accident_Mortality_(M)_for_plot_measure_by_years csv_data_file_for_2017_for indicator_Transport_Accident_Mortality_(M)_forplot_map_measure_by_regions csv_data_file_for_2017_for indicator_Transport_Accident_Mortality_(M)_forplot_measure_by_regions — csv_data_file_for_2015_for indicator_Transport_Accident_Mortality_(M)_for_plot_heatmap_across_indicators csv_data_file_for_2015_for indicator_Transport_Accident_Mortality_(M)_for_plot_measure_by_years csv_data_file_for_2015_for indicator_Transport_Accident_Mortality_(M)_forplot_map_measure_by_regions csv_data_file_for_2015_for indicator_Transport_Accident_Mortality_(M)_forplot_measure_by_regions Share this:LinkedInFacebookTwitterSkypeWhatsAppRedditPinterestPrintTumblrPocket
Jan 22
Must watch courses on Multiple Object Tracking.
This video is part of a lecture series about Multiple Object Tracking. It has six parts,
1. Introduction to Multi-object Tracking, https://www.youtube.com/watch?v=ay_QL… 2. Single-object Tracking in Clutter, https://www.youtube.com/watch?v=UpXpU… 3. Tracking n Objects in Clutter, https://www.youtube.com/watch?v=MdW25… 4. Random Finite Sets, https://www.youtube.com/watch?v=y3nIz… 5. MOT Using Conjugate Priors, https://www.youtube.com/watch?v=m3dso… 6. Outlook – What’s Next?, https://www.youtube.com/watch?v=rolck…
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Jan 22
Startup News : Bangladesh
Jan 12
Wall Street Visionaries Provide Chilling Views on Next Big Risk
Wall Street Visionaries Provide Chilling Views on Next Big Risk
“I worry more about nonfinancial companies than I do about financial companies”
“When you take away from people the hope to realize their potential, that is the epitome of despair”
“Do you really care about GDP? Is that how you’re gauging the quality of your life?”
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Jan 08
The Scientist and Engineer’s Guide to Digital Signal Processing
http://www.dspguide.com/eightres.htm
https://www.analog.com/media/en/technical-documentation/dsp-book/dsp_book_Ch1.pdf
Replace
" dsp_book_Ch1.pdf with dsp_book_Ch2.pdf, dsp_book_Ch3.pdf …. dsp_book_Ch10.pdf, …………, dsp_book_Ch33.pdf to read all the chapters. The authors kept them open as I saw.
Eight good reasons for learning DSP
(and how this book will help you do it)
- It’s the future!
Think how electronics has changed the world in the last 50 years. DSP will have the same role over the next 50 years. Learn it or be left behind! - DSP can snatch success from the jaws of failure
Let Steve Smith tell you about three examples from his own career. - Excellent graphics- over 500 figures, graphs, and illustrations
"
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