Today I am going to share Complete Guide To Become Data Scientist Free of Cost-II.
Hope you went through my previous post. If not then please check below first i.e.
So lets start with
Another most important aspect of Data Scientist is Data Visualization. You can check below resources for that
- Data Visualization in Python (Video Series). Very good tutorial on Data Visualization using matplotlib library in Python.
- Data Visualization in R (Video Series). Very good tutorial on Data Visualization using ggplot library in R.
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LINEAR ALGEBRA AND MULTI VARIABLE CALCULUS
It is important for the data scientist to have the knowledge in this field as sometimes data scientist carry out the implementation in own house and at that time this knowledge works.
You can check below resources
- Linear Algebra (Khan Academy).Practical linear algebra lessons from Khan Academy. Recommended for heavy data applications.
- Linear Algebra (MIT OpenCourseWare). Recommended for R&D data applications.
- Matrix Algebra Review (PDF). Can be used as a reference.
- Multi variable Calculus (Khan Academy). Practical multi variable calculus lessons from Khan Academy. Recommended for heavy data applications.
- Multivariable Calculus (MIT OpenCourseWare). Recommended for R&D data applications.
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Data collection is the process of gathering and measuring information on targeted variables in an established systematic fashion, which then enables one to answer relevant questions and evaluate outcomes.
It consist of two things one is API tutorials and other one is Web scraping tutorials.
You can check below resources for API tutorial i.e.
- Python: Quickstart Requests Guide (Tutorial).Shows how to request data from API’s using request library.
- R: httr Quickstart Guide (Tutorial).Shows how to request data from API’s using httr library.
For Web Scraping tutorials you can check below resources
- Python: Basic HTML Scraping (Tutorial). Its a basic tutorial on web scraping with the lxml and requests libraries.
- Python: Beautiful Soup (Tutorial).Contains Popular library for parsing web pages (beautiful soup replaces lxml).
- R: rvest (Tutorial). Shows basic web scraping techniques with the rvest library.
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This is the most important part of Data Scientist. You can check below resources for the same :
Python: scikit-learn quickstart (Tutorial) .Introduction to the sklearn package in Python and shows how algorithm are implemented.
R: caret package webinar (Video) .Introduction to the caret package in R and shows how algorithm are implemented.
Harvard’s CS 109: Data Science (Course) .Must recommended course which covers several machine learning models in python.
Machine Learning by Andrew Ng (Video Series) : Very practical approach to learn machine language.
An Introduction to Statistical Learning in R (PDF) : You can keep this book as reference guide.
This is all I have but this is not the end If you have something then please share with us in comment section.
It will be helpful for me as well as other readers.
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Author: Poonam Kaushal
A blogger and passionate writer who always try to introduce new concepts to readers.Involved in blogging since 2014 and believe in “No pain No gain” if you have to achieve something then you need to work hard.Working as freelance blogger in many companies and also managing her own blog that you all know savenlike.com.