Category Archives: Research

Statistics, Data Science, T-test, Alpha value, Critical Value

https://statisticsbyjim.com/hypothesis-testing/hypothesis-tests-significance-levels-alpha-p-values/

https://towardsdatascience.com/statistical-significance-hypothesis-testing-the-normal-curve-and-p-values-93274fa32687

https://statisticsbyjim.com/glossary/significance-level/

https://blog.minitab.com/blog/adventures-in-statistics-2/understanding-hypothesis-tests-significance-levels-alpha-and-p-values-in-statistics

 

https://towardsdatascience.com/statistical-tests-when-to-use-which-704557554740

 

 

https://blog.minitab.com/blog/alphas-p-values-confidence-intervals-oh-my

 

https://www.geo.fu-berlin.de/en/v/soga/Basics-of-statistics/Hypothesis-Tests/Introduction-to-Hypothesis-Testing/Critical-Value-and-the-p-Value-Approach/index.html

 

How to Find the T Critical Value in Excel

 

https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/find-sample-size/

 

https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/confidence-interval/

 

https://www.statisticshowto.datasciencecentral.com/degrees-of-freedom/

 

https://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/one-sample-t-interval-mean/v/introduction-to-t-statistics

 

http://evolution.gs.washington.edu/gs560/2011/lecture3.pdf

 

best youtube video

What is statistics?

Statistics is the art of dealing with Data of:
a. large amounts
b. error-tagged
Statistics is divided into two parts:
16 Introductory Data Analysis – HIS
1. Descriptive statistics:
• Calculating characteristic values: mean, median, standard deviation
• Graphical representation
2. Pedictive statistics: that tries to predict facts about large populations or about manufacturing
processes from observed/ measured facts in a small (produced) sample.

Mission Machine Learning

Pagerank Algorithm Eigenvalue

 

Square Matrices

 

 

Geometric Interpretation

 

Eigenvalue:

https://www.khanacademy.org/math/linear-algebra/alternate-bases/eigen-everything/v/linear-algebra-introduction-to-eigenvalues-and-eigenvectors

 

IEEE Reference Style

http://libraryguides.vu.edu.au/ieeereferencing/gettingstarted

Statistik, probability

 

 

Word Embeddings

Word2Vec, Unigram, NGram

 

 

 

 

Top 27+ Free Software for Text Analysis, Text Mining, Text Analytics: Review of Top 27 Free Software for Text Analysis, Text Mining, Text Analytics includingGeneral Architecture for Text Engineering ? GATE, RapidMiner Text Mining Extension, KH Coder, VisualText, Datumbox, TAMS, QDA Miner Lite, Carrot2, CAT, GATE, tm, Gensim, Natural Language Toolkit, Unstructured Information Management Architecture, OpenNLP, KNIME, Orange-Textable, LPU, Apache Mahout, Pattern, LingPipe, S-EM, LibShortText, Twinword, Apache Stanbol, Aika, Distributed Machine Learning Toolkit and Coh-Metrix.

 

 

Must see this:

Word embeddings are a modern approach for representing text in natural language processing. Embedding algorithms like word2vec and GloVe are key to the state-of-the-art results achieved by neural network models on natural language processing problems like machine translation. In this tutorial, you will discover how to train and load word embedding models for natural language ?

 

Real Life AI projects

Machine Learning Scikit Learn

Machine Learning with Python

 

Natural Language Processing, Text Summarization,

 

 

 

Neural Network: Machine Learning

 

BigData Basics and Tools

Machine Learning Mastery

The Naive Bayes algorithm is simple and effective and should be one of the first methods you try on a classification problem. In this tutorial you are going to learn about the Naive Bayes algorithm including how it works and how to implement it from scratch in Python. Update: Check out the follow-up on tips for …

 

Machine Learning in MATLAB: KNN