List of available data set for Data Scientist

I am exploring on data related to 2019nCoV and found the following list of dataset that can be used for data scientist, data scientist to be, student, etc to explore. Check it out

1. https://data.world/
2. https://quantumstat.com/dataset/dataset.html
3. https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/virus?SeqType_s=Nucleotide&VirusLineage_ss=Wuhan%20seafood%20market%20pneumonia%20virus,%20taxid:2697049
4. https://www.ncbi.nlm.nih.gov/genbank/2019-ncov-seqs/?utm_campaign=wuhan_nCoV&utm_source=twitter&utm_medium=referral
5. https://www.ncbi.nlm.nih.gov/nuccore/MN908947,MN970003,MN970004,MN938384,MN938385,MN938386,MN938387,MN938388,MN938389,MN938390,MN975262,MN975263,MN975264,MN975265,MN975266,MN975267,MN975268,MN985325,MN988713,MN994467,MN994468,MN997409,MN988668,MN988669
6. https://researchguides.uic.edu/c.php?g=252253&p=1683071
7. https://archive.org/details/2019-search-engine-keyphrases.json

or you can just use google and search the entire internet through the engine
https://datasetsearch.research.google.com/

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List of Data Sciences and Machine Learning usefull link

Credit to: Shivam Panchal
As published by Shivam at Linked @ https://www.linkedin.com/pulse/data-science-machine-learning-beginners-path-shivam-panchal/

Platforms:

1. What Is Hadoop? Hadoop Tutorial For Beginners https://youtu.be/n3qnsVFNEIU
2. What is Apache Spark? The big data analytics platform explained http://www.techworld.com.au/article/629920/what-apache-spark-big-data-analytics-platform-explained/
3. Apache Spark Tutorial: ML with PySpark https://www.datacamp.com/community/tutorials/apache-spark-tutorial-machine-learning
4. A Beginner's Guide To Apache Pig https://hortonworks.com/tutorial/beginners-guide-to-apache-pig/
5. Realtime Event Processing in Hadoop with NiFi, Kafka and Storm https://hortonworks.com/tutorial/realtime-event-processing-in-hadoop-with-nifi-kafka-and-storm/

Math:

1. A Deep Dive Into Linear Algebra https://www.khanacademy.org/math/linear-algebra
2. An Introduction to Combinatorics & Graph Theory https://www.whitman.edu/mathematics/cgt_online/cgt.pdf

Tools & Framework:

1. TensorFlow Tutorial – Deep Learning Using TensorFlow https://youtu.be/yX8KuPZCAMo
2. A 6-part introduction to the MXNet API https://becominghuman.ai/an-introduction-to-the-mxnet-api-part-1-848febdcf8ab
3. Keras Tutorial: The Ultimate Beginner's Guide to Deep Learning in Python https://elitedatascience.com/keras-tutorial-deep-learning-in-python

Data Visualization:

1. Building Python Data Apps with Blaze and Bokeh https://youtu.be/1gD9LMqREDs
2. Matplotlib Tutorial: Python Plotting https://www.datacamp.com/community/tutorials/matplotlib-tutorial-python
3. Python Bokeh Tutorial - Creating Interactive Web Visualizations https://youtu.be/Mz1AXUE0nR4

Concepts:

1. Simple Linear Regression https://onlinecourses.science.psu.edu/stat501/node/250
2. Simple and Multiple Linear Regression in Python https://medium.com/towards-data-science/simple-and-multiple-linear-regression-in-python-c928425168f9
3. Linear Regression in R https://www.tutorialspoint.com/r/r_linear_regression.htm
4. An Introduction To Logistic Regression http://ufldl.stanford.edu/tutorial/supervised/LogisticRegression/
5. Building A Logistic Regression in Python, Step by Step by Susan Li https://medium.com/towards-data-science/building-a-logistic-regression-in-python-step-by-step-becd4d56c9c8
6. Supervised and Unsupervised Machine Learning Algorithms https://machinelearningmastery.com/supervised-and-unsupervised-machine-learning-algorithms/
7. 6 Easy Steps to Learn Naive Bayes Algorithm (with codes in Python and R) https://www.analyticsvidhya.com/blog/2017/09/naive-bayes-explained/
8. A Tutorial on Support Vector Machines for Pattern Recognition http://www.cs.northwestern.edu/~pardo/courses/eecs349/readings/support_vector_machines4.pdf
9. A Complete Tutorial on Tree Based Modeling from Scratch (in R & Python) https://www.analyticsvidhya.com/blog/2016/04/complete-tutorial-tree-based-modeling-scratch-in-python/

Python:

1. A Complete Tutorial to Learn Data Science with Python from Scratch https://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-learn-data-science-python-scratch-2/
2. NumPy Tutorial: Data analysis with Python https://www.dataquest.io/blog/numpy-tutorial-python/
3. Scipy Tutorial: Vectors and Arrays (Linear Algebra) https://www.datacamp.com/community/tutorials/python-scipy-tutorial
4. Python Pandas Tutorial https://www.tutorialspoint.com/python_pandas/
5. Machine Learning with scikit learn Part 1 & 2 https://youtu.be/2kT6QOVSgSghttps://youtu.be/WLYzSas511I

CS:

1. A Thorough Overview of Computational Logic https://www.cs.utexas.edu/users/boyer/acl.pdf

Game Theory:

1. Game Theory - A 3 Part Introduction https://youtu.be/x8gOi7D6QeQ

Statistics:

1. Correlation & causality https://www.khanacademy.org/math/probability/scatterplots-a1/creating-interpreting-scatterplots/v/correlation-and-causality
2. Analysis of variance (ANOVA) https://www.khanacademy.org/math/statistics-probability/analysis-of-variance-anova-library
3. Understanding Hypothesis Tests: Significance Levels (Alpha) and P values in Statistics https://shar.es/1PANrc
4. Characteristics of Good Sample Surveys and Comparative Studies https://onlinecourses.science.psu.edu/stat100/node/3
5. Descriptive and Inferential Statistics https://www.thoughtco.com/differences-in-descriptive-and-inferential-statistics-3126224
6. Intro to Probability Theory https://youtu.be/f9XFM8YLccg
7. Introduction to Conditional Probability & Bayes theorem for data science https://www.analyticsvidhya.com/blog/2017/03/conditional-probability-bayes-theorem/
8. Central limit theorem https://www.khanacademy.org/math/statistics-probability/sampling-distributions-library/sample-means/v/central-limit-theorem

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