Prashant Singh Rana, PhD
Associate Professor,
Computer Science & Engg Dept,
Thapar Institute of Engg & Tech,
Patiala, Punjab  147004, India.
Director & CoFounder,
Resource
Click Here to join Rana Research Group for ML / DL News, Article, Internship, Code and more.....
Click Here (Paper with Codes) for Gold Mine for Deep Learning Resource
(Computer Vision, NLP, Speech, Video, Robotics....... )
UNIT I : Learn Python
1. Learn Basics of Python in 2 hr  Click Here
It contains 16 basic programs in python that help to understand the syntax, loops, conditional checking, data structures, file handling in python.
3. Python Libraries: NumPy, Scipy, Matplotlib, Pandas, OpenCV
Specialized libraries for python for various operations such as interpolation, optimization, linear algebra, signal processing, Fourier transformation, etc

NumPy

Scipy

matplotlib

Special Matrices (Must Try)
4. Basic plotting and visualization using Python
Specialized libraries for python for various operations such as interpolation, optimization, linear algebra, signal processing, Fourier transformation, etc.
Click Here
5. Basic of Pandas
Pandas is a highlevel data manipulation tool developed by Wes McKinney. It is built on the Numpy package and its key data structure is called the DataFrame. DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables.
Tutorial1 Tutorial2
6. Python packages for research
For research on Scientific/Engineering problems such as AI, Bioinformatics, Chemistry, Electronics Design, GIS, Human Machine Interface, Image Recognition, NPL, etc.
Click Here
UNIT II : Python for Machine Learning, Optimization & Multithreading
1. Machine Learning using Python
http://scikitlearn.org
2. Python Code for Optimization
Genetic Algorithm, PSO and DE code in python.
Click Here to download
3. Multithreading using Python
Convert 100 text files to upper case using multithreading.
Click Here to download
4. Graph Theory using Python
Algorithm and Problems
Graph Tools → Click Here  Tutorial
iGraph → Click Here  Tutorial
NetworkX → Click Here  Tutorial
UNIT III : Learn R
1. Download & Install R and RStudio
R → Click Here to download
RStudio → Click Here to download
2. Learn Basics of R in 2 hr
It contains 17 basic programs in R that help to understand the syntax, loops, conditional checking, file handling and basic plotting.
Click Here to download.
3. Basic plotting and visualization using R
Specialized libraries for python for various operations such as interpolation, optimization, linear algebra, signal processing, Fourier transformation, etc
Click Here
4. [Book] R for Everyone  Advanced Analytics and Graphics
Specialized libraries for python for various operations such as interpolation, optimization, linear algebra, signal processing, Fourier transformation, etc
Click Here
5. R For Computer Networks
Those who are interested in Computer Networks (Security, Modelling, Analysis, Simulation, and many more). Kindly explore the following books.
6. R Packages for research
For research on Scientific/Engineering problems such as AI, Bioinformatics, Chemistry, Electronics Design, GIS, Human Machine Interface, Image Recognition, NPL, etc.
Click Here
UNIT IV : R for Machine Learning
1. Books
Books on R, Python, Machine Click Here to exploreLeaning, Big Data Analytics.

01  The Machine Learning  Starter Kit

02  Data Mining with Rattle and R

03  Elements of Statistical Learning data mining, inference and prediction

04  An Introduction to Statistical Learning with Applications in R

05  Applied Predictive Modeling

07  R for Everyone Advanced Analytics and Graphics

08  Reproducible Research with R and RStudio

Explore "Others Books on Machine Learning"

Explore "BooksMathsLinear LagebraProbalility"

Explore "BooksSoftcomputing"
2. Sample Datset
It contains Data set for Machine Learning practical.
Click Here to download
3. Machine Learning Models Code in R
Machine Learning Models using R Coding + Hands on R programming.
Click Here to download
4. Machine Learning Models in R
Click Here to explore
5. Rattle Videos
Videos on Rattle, R Studio, Create R Package
Click Here to explore
UNIT V : Important Resources for Machine Learning
1. Machine Learning MOOCs on Coursera.org
Recommeded courses from University of Washington.
Click Here to explore
2. Expert Talks (Videos) on Big Data
Learn Big Data Analytics using Top YouTube Videos, TED Talks & other resources
Click Here to explore
3. The Talking Machines
Discussion on latest topics on Machine learning people from Academics / Industry.
Click Here to explore
4. Blog @ Machine Learning Mastery.
Great Blogs.
Click Here to explore
5. Data Set for Machine Learning
Link1: Quora
Link2: Google DataSet toolbox
Link3: Sample Dataset
6. Machine Learning Competitions (Crowd Analytics)
Helpful in selecting research topics.

TunedIt

ChaLearnLap

Innocentive

DreamChallenges

CrowdAnalytix

DataHack@AnalyticsVidhya

Numer.ai

GenomeInterpretation

GrandChallenges
7. Join Mailing Group

http://bit.ly/MachineLearningBlogAndResource

http://feedburner.google.com/fb/a/mailverify?uri=analyticsvidhya

http://www.innocentive.com/blog

https://www.crowdanalytix.com/blog

http://www.kdnuggets.com/news/subscribe.html

http://www.rbloggers.com/blogslist/
8. Mathematics for Machine Learning

Special Matrices(Must Try)

Workshop on R. Click Here

Introduction to linear algebra with R. Click Here

Skills Required for Machine Learning jobs. Click Here

How to improve maths skills? Click Here

Self Evaluation in maths for machine learning. Click Here

[Book] Linear Lagebra & Probalility. Click Here
UNIT VI: Gold Mine for Researchers (Free Books, Papers, Thesis)
1. For Research Papers
Search using DOI (Digital Object Identifier).
Example (Search for): 10.1016/j.bbapap.2014.07.010
2. For Books
3. For Thesis  ProQuest
4. Paper with Code  Click Here  Most Important
5. Two Minutes Papers  Click Here
6. Explore

Google Dataset Search  Click Here

Explore Kaggle (Compete, Datasets, Notebooks, Jobs, more)  Click Here

UCI dataset for Regression, Classification, Clustering, etc  Click Here
Most Important ............
"If you give 100 hours per week, you can complete your PhD in three years"  Prof. Bhim Singh, IIT Delhi.
Finally

"Mathematics is the queen of all the sciences"  Anonymous

Whenever you have time, solve/explore maths problems, solve/explore graph problems, do maths using R/Python/Matlab/Octave, explore competitions, explore dataset.

"Great minds discuss ideas, Average minds discuss events, Small minds discuss people"

"Success is a journey...not a Destination!!!!"