Apply Data Science
to real world problems

Insights from a decade of IT industry experience

Learning Resources

Accelerate your learning by applying Interpretations of data science concepts from industry point of view.

Python
Programming

Learn the absolute basics of programming with Python for Machine Learning

Python
AI/ML

Learn how AI/ML algorithms work. How to implement it for real life scenarios.

Python
Case studies

End to End Machine Learning case studies solved using python

Albert Einstein

Imagination is more important than knowledge

Albert Einstein

Latest Blogs

Thoughts, ideas and tutorials about Data Science

How to do Sampling in R
Stats 101: How to do sampling in R?
To perform sampling in R, one can take help of various functions available for each type of sampling technique.
Read more.
Sampling Theory
Stats 101: What is the ​Sampling Theory
Sampling means choosing random values. A random sample exhibits the properties of the whole population.
Read more.
Measures of Location [Quartiles]
Stats 101: Measures of Location [Quartiles]
Measures of location is a combination of values for a data which can summarise its distribution.
Read more.
Standard Deviation
Stats 101: Measures of Spread [Standard Deviation]
Standard Deviation helps to understand 'On an average, how far away each data point is from the mean value'
Read more.
Stats 101: Measures of Spread [Min Max]
It is very important to explore the data and understand it, before you can use it for solving problems.
Read more.
Stats 101: What is Mode value and when to use it?
Mode is the most frequently occurring value in a set.
Read more.
Stats 101: Why Median is a better measure of central tendency
When you are trying to understand about the central tendency of a numeric dataset, the median is a better way
Read more.
Stats 101: Why Mean is Misleading?
The average age of people living in that area is 49 Years Will you launch the dating app?
Read more.

My story

Hi!

My name is Farukh Hashmi. Currently I am working as a Lead Data Scientist at Saama Technologies. I have 11+ years of IT industry experience in AI, Machine Learning, Data Science and BI.

I have built predictive and prescriptive models for various business domains like Logistics, Insurance, Telecom and Consumer Packaged Goods while working with some of the technology leaders like Infosys, IBM, and Persistent Systems.

I have started this blog to connect the dots of theory and practical applications of AI/Machine Learning for all the budding Data Scientists out there!