On Bloomberg Today: Of Interest #Root

China Has Rare Earths Plan Ready to Go If Trade War Deepens

https://www.bloomberg.com/news/articles/2019-05-31/china-has-a-rare-earths-plan-ready-to-go-if-trade-war-deepens?srnd=premium

A 600-Page Textbook About Modern Monetary Theory Has Sold Out

https://www.bloomberg.com/news/articles/2019-05-31/a-600-page-textbook-about-modern-monetary-theory-has-sold-out?srnd=premium

Flying Has Become More Dangerous. Don’t Just Blame Boeing

https://www.bloomberg.com/news/articles/2019-05-30/flying-has-become-more-dangerous-don-t-just-blame-boeing?srnd=premium

Apple to Reveal Glimpses of Its Next Era of Apps and Devices

https://www.bloomberg.com/news/articles/2019-05-31/apple-s-future-ios-13-macos-10-15-watchos-6-tvos-13-mac-pro?srnd=premium

China Has Rare Earths Plan Ready to Go If Trade War Deepens

https://www.bloomberg.com/news/articles/2019-05-31/china-has-a-rare-earths-plan-ready-to-go-if-trade-war-deepens?srnd=premium

China Threatens Sweeping Blacklist of Firms After Huawei Ban

https://www.bloomberg.com/news/articles/2019-05-31/china-to-set-up-unreliable-entity-list-after-u-s-huawei-ban?srnd=premium

—-

Sayed Ahmed

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Blog: http://sitestree.com, http://bangla.salearningschool.com From: https://sitestree.com/on-bloomberg-today-of-interest/
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Post Data:2019-05-31 08:51:50

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Hiring and Skills #Root

WHY YOU SHOULD THINK TWICE BEFORE HIRING BASED ON SKILLS

https://www.cornerstoneondemand.com/rework/why-you-should-think-twice-hiring-based-skills

Disadvantages of Skill-Based Pay – USI

https://lnkd.in/eHZHu-5

The advantages and pitfalls of the modern hiring process

https://mashable.com/2015/01/22/modern-hiring-problems/

The Pros And Cons Of Pre-Employment Testing

https://www.jumpstartinc.org/pros-cons-pre-employment-testing From: http://sitestree.com/hiring-and-skills/
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Post Data:2019-05-29 20:57:02

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Natural Language Processing Resources #Root

Regular Expressions, Text Normalization, Edit Distance

http://web.stanford.edu/~jurafsky/slp3/2.pdf

Language Modeling with N-Grams
http://web.stanford.edu/~jurafsky/slp3/3.pdf

Slide: https://web.stanford.edu/class/cs124/lec/languagemodeling2019.pdf

Chapter 4, "Naive Bayes and Sentiment Classification"
http://web.stanford.edu/~jurafsky/slp3/4.pdf
Slide: https://web.stanford.edu/class/cs124/lec/naivebayes.pdf

Thumbs up? Sentiment Classification using Machine Learning Techniques

http://www.cs.cornell.edu/home/llee/papers/sentiment.pdf

Lexicons for Sentiment, Affect, and Connotation
http://web.stanford.edu/~jurafsky/slp3/19.pdf

Logistic Regression
http://web.stanford.edu/~jurafsky/slp3/5.pdf

https://spark-public.s3.amazonaws.com/cs124/slides/ir-1.pdf

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Post Data:2019-05-26 13:23:35

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WordPress: Hide Date and Author from your posts #Root

Yes, it is WordPress. Positively, you can think it to be similar to embedded programming (not inside hardware but inside a software)

Options:
Use Plugins such as

1. WP Meta and Date Remover
2. WP Post Date Remover.

The plugins after installing will remove post date. However, you might need to add custom CSS for removing other meta information such as Author, Category, the words by and/or in.

The first plugin 1. WP Meta and Date Remover also have the option to write down custom css. The 2nd plugin might have that option – I did not explore. plugin 1 has better rating than 2.

You can even remove post dates just by customizing WordPress theme CSS. You can create a child theme and customize the CSS. Note, you do not want to modify the core theme css files because any WordPress update will overwrite your changes.

The following CSS classes worked with Plugin 1. However, the same CSS should work if written inside custom CSS file of the child theme.

/* Ref: The first four lines came with the plugin 1, rest I wrote*/
.entry-meta {display:none !important;}

.home .entry-meta { display: none; }
.entry-footer {display:none !important;}
.home .entry-footer { display: none; }

.post-date {
display:none !important;
}

li.byline {
color: #FFFFFF !important;
}

span.author {
display: none !important;
}

li.byline .terms {
color: #0000 !important;
}

[id^=post] {
padding-left:30px !important;
padding-right:30px !important;
}

Note: Just because I wrote it, does not mean that I want to work with WordPress/CSS. I do not want to.

Sayed Ahmed
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Blog: http://sitestree.com, http://bangla.salearningschool.com From: http://sitestree.com/wordpress-hide-date-and-author-from-your-posts/
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Post Data:2019-05-17 12:43:30

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LDA: Latent Dirichlet Allocation (LDA): Applications of LDA #Root

What is LDA topic modeling?

"Latent Dirichlet Allocation (LDA) is an example of topic model and is used to classify text in a document to a particular topic"

https://towardsdatascience.com/topic-modeling-and-latent-dirichlet-allocation-in-python-9bf156893c24

What is topic modeling used for?
"In machine learning and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body."

Topic model – Wikipedia
https://en.m.wikipedia.org/wiki/Topic_model

Is LDA supervised or unsupervised?
"Original LDA is unsupervised learning algorithm, while Labeled-LDA and Multi-Grain LDA, another topic model for classification and sentiment analysis, are supervised algorithm."

https://www.quora.com/Is-LDA-latent-dirichlet-allocation-unsupervised-or-supervised-learning

Modeling healthcare data using multiple-channel latent Dirichlet allocation
https://www.sciencedirect.com/science/article/pii/S1532046416000253

Latent Dirichlet Allocation for Classification using Gene Expression Data
https://ieeexplore.ieee.org/document/8251263

A hybrid LDA and genetic algorithm for gene selection and classification of microarray data
https://www.sciencedirect.com/science/article/pii/S0925231210002456

LDA and Magazine Similarity
https://www.youtube.com/watch?v=3mHy4OSyRf0

LDA Applications on Scripts from Friends
https://medium.com/@sherryqixuan/topic-modeling-and-pyldavis-visualization-86a543e21f58
https://towardsdatascience.com/topic-modeling-and-latent-dirichlet-allocation-in-python9bf156893c24

LDA on Kaggle Dataset
https://www.kaggle.com/therohk/million-headlines/data
https://gist.github.com/davidandrzej/939840 From: https://sitestree.com/lda-latent-dirichlet-allocation-lda-applications-of-lda/
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Post Data:2019-05-16 12:07:27

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On LDA: LDA and Healthcare #Root

What is LDA topic modeling?

"Latent Dirichlet Allocation (LDA) is an example of topic model and is used to classify text in a document to a particular topic"

https://towardsdatascience.com/topic-modeling-and-latent-dirichlet-allocation-in-python-9bf156893c24

What is topic modeling used for?

"In machine learning and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body."

Topic model – Wikipedia

https://en.m.wikipedia.org/wiki/Topic_model

Is LDA supervised or unsupervised?

"Original LDA is unsupervised learning algorithm, while Labeled-LDA and Multi-Grain LDA, another topic model for classification and sentiment analysis, are supervised algorithm."

https://www.quora.com/Is-LDA-latent-dirichlet-allocation-unsupervised-or-supervised-learning

Modeling healthcare data using multiple-channel latent Dirichlet allocation

https://www.sciencedirect.com/science/article/pii/S1532046416000253

Latent Dirichlet Allocation for Classification using Gene Expression Data

https://ieeexplore.ieee.org/document/8251263

A hybrid LDA and genetic algorithm for gene selection and classification of microarray data

https://www.sciencedirect.com/science/article/pii/S0925231210002456 From: https://sitestree.com/on-lda-lda-and-healthcare/
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Post Data:2019-05-16 11:31:54

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Want to become a self-driving car engineer: “12 PROJECTS THAT HELP YOU BECOME SELF-DRIVING CAR ENGINEER (PYTHON and C++ CODE AVAILABLE)” #Root

Want to become a self-driving car engineer: “12 PROJECTS THAT HELP YOU BECOME SELF-DRIVING CAR ENGINEER (PYTHON and C++ CODE AVAILABLE)”

Project 1 – Finding Lane Lines on the Road

https://github.com/ndrplz/self-driving-car/tree/master/project_1_lane_finding_basic

Project 2 – Traffic Sign Classification

https://github.com/ndrplz/self-driving-car/tree/master/project_2_traffic_sign_classifier

Project 3 – Behavioral Cloning

https://github.com/ndrplz/self-driving-car/tree/master/project_3_behavioral_cloning

Project 4 – Advanced Lane Finding

https://github.com/ndrplz/self-driving-car/tree/master/project_4_advanced_lane_finding

Vehicle Detection Project

https://github.com/ndrplz/self-driving-car/tree/master/project_5_vehicle_detection

Extended Kalman Filter Project

https://github.com/ndrplz/self-driving-car/tree/master/project_6_extended_kalman_filter

Unscented Kalman Filter Project Starter Code

https://github.com/ndrplz/self-driving-car/tree/master/project_7_unscented_kalman_filter

Kidnapped Vehicle

https://github.com/ndrplz/self-driving-car/tree/master/project_8_kidnapped_vehicle

keeping the car on track by appropriately adjusting the steering angle.

https://github.com/ndrplz/self-driving-car/tree/master/project_9_PID_control

Model-predictictive control: CarND-Controls-MPC

https://github.com/ndrplz/self-driving-car/tree/master/project_10_MPC_control

Path Planning

https://github.com/ndrplz/self-driving-car/tree/master/project_11_path_planning

Road Segmentation

https://github.com/ndrplz/self-driving-car/tree/master/project_12_road_segmentation

https://github.com/ndrplz

Reference:

https://www.linkedin.com/feed/update/activity:6530021235290664960/ From: http://sitestree.com/want-to-become-a-self-driving-car-engineer-12-projects-that-help-you-become-self-driving-car-engineer-python-and-c-code-available/
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Post Data:2019-05-07 19:36:51

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AI Implementation Platforms: Reinforcement Learning Platforms and Applications: #Root

"

Gym:
https://gym.openai.com/

Gym is a toolkit for developing and comparing …. It supports teaching agents everything from walking to playing games like Pong or Pinball.

"
https://gym.openai.com/

—-

"Project Malmo integrates (deep) reinforcement learning, cognitive science, and many ideas from artificial intelligence. "

https://www.microsoft.com/en-us/research/project/project-malmo/

—-

DeepMind:
"DeepMind’s scientific mission is to push the boundaries of AI, developing systems that can learn to solve any complex problem without needing to be taught how"
https://deepmind.com/blog/open-sourcing-deepmind-lab/

UCL Course on RL

http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html

Basics of RL

From: https://www.kdnuggets.com/2018/03/5-things-reinforcement-learning.html
"

  1. What is reinforcement learning? How does it relate with other ML techniques?

Reinforcement Learning(RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences.

  1. What are some most used Reinforcement Learning algorithms?

Q-learning and SARSA (State-Action-Reward-State-Action) are two commonly used model-free RL algorithms.

"

Uses of RL

" building AI for playing computer games"

" robotics and industrial automation "

"applications of RL include text summarization engines, dialog agents (text, speech) which can learn from user interactions and improve with time, learning optimal treatment policies in healthcare and RL based agents for online stock trading." From: https://sitestree.com/ai-implementation-platforms-reinforcement-learning-platforms-and-applications/
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Post Data:2019-05-03 12:42:43

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Reinforcement Learning: Tutorials: Code: Questions and Answers #Root

Reinforcement Learning: Tutorials: Code: Questions and Answers

Must Check: Questions and Answers:
https://www.inf.ed.ac.uk/teaching/courses/rl/tutorials.html

Check if you can find an equation here: Check the grid example
https://medium.com/@zsalloum/monte-carlo-in-reinforcement-learning-the-easy-way-564c53010511

TD: Temporal Difference
https://towardsdatascience.com/td-in-reinforcement-learning-the-easy-way-f92ecfa9f3ce

Not that good:
https://courses.cs.washington.edu/courses/csep573/12au/lectures/18-rl.pdf
http://incompleteideas.net/609%20dropbox/slides%20(pdf%20and%20keynote)/9-10-MC.pdf

From: https://sitestree.com/reinforcement-learning-tutorials-code-questions-and-answers/
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Post Data:2019-05-03 11:51:24

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Math and Probability for Data Science #Root

Math and Probability for Data Science

Esp. for Reinforcement Learning

Probability: cov(x,y): https://math.stackexchange.com/questions/1581773/computing-the-covariance-of-flipping-a-coin-in-the-first-and-last-flips

Fundamental Concept in Machine Learning
https://faculty.washington.edu/tamre/BayesTheorem.pdf

—-

Lecture Slides – old book
https://www.inf.ed.ac.uk/teaching/courses/rl/lecturelist.html


Color :
https://digitalsynopsis.com/design/color-thesaurus-correct-names-of-shades/

Random Sum:
http://www.math.unl.edu/~sdunbar1/ProbabilityTheory/Lessons/Conditionals/RandomSums/randsum.shtml

Simple probability examples:
http://jwilson.coe.uga.edu/emt668/emat6680.folders/dickerson/probability/titled.html
https://faculty.math.illinois.edu/~kkirkpat/SampleSpace.pdf

Series and Sum:
http://www.mathcentre.ac.uk/resources/uploaded/mc-ty-convergence-2009-1.pdf

Reference:
http://www.sjsu.edu/faculty/watkins/runs.htm

https://mathinsight.org/image/two_dice_distribution
http://www.mathguide.com/lessons2/ExpectedValues.html

http://www.mathguide.com/lessons2/ExpectedValues.html
https://www.texasgateway.org/resource/44-geometric-distribution-optional
https://www.me.utexas.edu/~jensen/ORMM/computation/unit/rvadd/discrete_dist/geometric.html
http://www.mathguide.com/lessons2/ExpectedValues.html
http://www.sjsu.edu/faculty/watkins/runs.htm From: https://sitestree.com/math-and-probability-for-data-science/
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Post Data:2019-05-03 11:45:31

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