Lecturing has been criticized as ineffective relative to other methods of teaching that involve students as active participants in the learning process, not as passive observers. Lectures, though, are a fact of academic life. They are the most widely used method of teaching in colleges and universities (McK

"https://undergrad.ucf.edu/whatsnext/wp-content/uploads/2016/03/Successful-Lecturing.pdf

—-
ALTERNATIVES TO LECTURE
https://ce.uwex.edu/wp-content/uploads/2017/05/Alternatives-to-Lecture.pdf

—-
Tips for Engaging Students in Learning:
https://www.mcgill.ca/skillsets/files/skillsets/inprovisation_engaging_small_and_large_groups-tips_for_engaging_students_in_learning-nov_2012_joan.pdf

—

CREATING SIGNIFICANT LEARNING EXPERIENCES

https://www.unl.edu/philosophy/%5BL._Dee_Fink%5D_Creating_Significant_Learning_Experi(BookZZ.org).pdf

—

Comparison of the effect of lecture and blended teaching methods on students’ learning and satisfaction

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4235559/

—-

Managing the Large Enrollment Course

https://serc.carleton.edu/introgeo/interactive/mgtlarge.html

—-

Best Practices for Large-Enrollment Online Courses, Part I

https://teachonline.asu.edu/2018/09/best-practices-for-large-enrollment-courses-in-canvas/
—

LEARNER CENTERED GRADING
https://www.faa.gov/training_testing/training/fits/guidance/media/lcg.pdf

—
Student-Oriented Grading
http://people.uleth.ca/~runte/grading/

—-
Addressing Student Misconceptions of the Grading Processhttp://people.uleth.ca/~runte/grading/AstudentC.htm

May 26

Natural Language Processing Resources

By Sayed in ব্লগ । Blog

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

Jure Leskovec, Anand Rajaraman, Jeff Ullman. 2014. Mining of Massive Datasets. Chapter 9 2nd edition. pages 307-311 (intro and 9.1) and 321-327 (9.3).
http://infolab.stanford.edu/~ullman/mmds/ch9.pdf
Web graphs, Links, and PageRank Videos

https://spark-public.s3.amazonaws.com/cs124/slides/web.pdf
- Networks, Crowds, and Markets: Reasoning About a Highly Connected World By David Easley and Jon Kleinberg Cambridge University Press (2010) Chapter 2, Sections 3.1-3.3 and Secs 18.1-18.5
- http://www.cs.cornell.edu/home/kleinber/networks-book/
- Reference:
- Course: CS 124: From Languages to Information
- http://web.stanford.edu/class/cs124/
Sayed Ahmed

Linkedin: https://ca.linkedin.com/in/sayedjustetc

Blog: http://sitestree.com, http://bangla.salearningschool.com

May 17

Reinforcement Learning Concepts Explained in a Simple Way.

By Sayed in AI ML DS RL DL NN NLP Data Mining Optimization, ব্লগ । Blog

Reinforcement Learning Concepts Explained in a Simple (or not) Way.

This is intended for the beginners who want to know the concepts used in Reinforcement Learning i.e. Interactive Learning.

Reinforcement Learning is also one aspect of Machine Learning, Data Science, and AI

Summary of Tabular Methods in Reinforcement Learning

Comparison between the different tabular methods in Reinforcement Learning

https://towardsdatascience.com/summary-of-tabular-methods-in-reinforcement-learning-39d653e904af

—

Silver — Lecture 6: Value Function Approximation

https://medium.com/@SeoJaeDuk/archived-post-rl-course-by-david-silver-lecture-6-value-function-approximation-241695feeb1f

—-

Going Deeper Into Reinforcement Learning: Understanding Q-Learning and Linear Function Approximation (might not be simple/easy)

https://danieltakeshi.github.io/2016/10/31/going-deeper-into-reinforcement-learning-understanding-q-learning-and-linear-function-approximation/

Reinforcement in Psychology

"Understanding Reinforcement in Psychology. Reinforcement is a term used in operant conditioning to refer to anything that increases the likelihood that a response will occur. … Reinforcement can include anything that strengthens or increases a behavior, including specific tangible rewards, events, and situations."

What Is Reinforcement in Operant Conditioning? – Verywell Mind

https://www.verywellmind.com/what-is-reinforcement-2795414

Introduction to Reinforcement Learning

https://towardsdatascience.com/introduction-to-reinforcement-learning-chapter-1-fc8a196a09e8

Solving the Multi-Armed Bandit Problem

https://towardsdatascience.com/solving-the-multi-armed-bandit-problem-b72de40db97c

My Journey to Reinforcement Learning — Part 2: Multi-Armed Bandit Problem

https://towardsdatascience.com/my-journey-to-reinforcement-learning-part-2-multi-armed-bandit-problem-eefe1afab73c

Self Learning AI-Agents Part I: Markov Decision Processes

https://towardsdatascience.com/self-learning-ai-agents-part-i-markov-decision-processes-baf6b8fc4c5f

Reinforcement Learning Demystified: Markov Decision Processes (Part 1)

https://towardsdatascience.com/reinforcement-learning-demystified-markov-decision-processes-part-1-bf00dda41690

Reinforcement Learning Demystified: Solving MDPs with Dynamic Programming

https://towardsdatascience.com/reinforcement-learning-demystified-solving-mdps-with-dynamic-programming-b52c8093c919

Planning by Dynamic Programming: Reinforcement Learning

https://towardsdatascience.com/planning-by-dynamic-programming-reinforcement-learning-ed4924bbaa4c

Monte Carlo: Reinforcement Learning for Meal Planning based on Meeting a Set Budget and Personal Preferences (Monte Carlo)
https://towardsdatascience.com/reinforcement-learning-for-meal-planning-based-on-meeting-a-set-budget-and-personal-preferences-9624a520cce4

Monte Carlo Simulations with Python (Part 1)

https://towardsdatascience.com/monte-carlo-simulations-with-python-part-1-f5627b7d60b0

Monte Carlo Without the Math

https://towardsdatascience.com/monte-carlo-without-the-math-90630344ff7b

Simple Reinforcement Learning: Temporal Difference Learning

https://towardsdatascience.com/simple-reinforcement-learning-temporal-difference-learning-53d1b3263d79

Model-Free Prediction: Reinforcement Learning

https://towardsdatascience.com/model-free-prediction-reinforcement-learning-507297e8e2ad

What exactly is bootstrapping in reinforcement learning?

https://datascience.stackexchange.com/questions/26938/what-exactly-is-bootstrapping-in-reinforcement-learning

n-step bootstrapping

http://ipvs.informatik.uni-stuttgart.de/mlr/wp-content/uploads/2018/06/18-RL-nstep.pdf

Planning and Learning with Tabular Methods

https://medium.com/@SeoJaeDuk/archived-post-planning-and-learning-with-tabular-methods-8-1-8-4-bf8f836614d0

Sayed Ahmed

Linkedin: https://ca.linkedin.com/in/sayedjustetc

Blog: http://sitestree.com, http://bangla.salearningschool.com

May 17

WordPress: Hide Date and Author from your posts

By Sayed in ব্লগ । Blog

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
Linkedin: https://ca.linkedin.com/in/sayedjustetc

Blog: http://sitestree.com, http://bangla.salearningschool.com

May 16

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

By Sayed in ব্লগ । Blog

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

May 16

On LDA: LDA and Healthcare

By Sayed in ব্লগ । Blog

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

May 07