Ultimate guide to handle Big Datasets for Machine Learning using Dask (in Python)
Introduction Have you ever tried working with a large dataset on a 4GB RAM machine? It starts heating up while doing simplest of machine …
pandas
Swiftapply – A Python Package for Efficient and Superfast use of Pandas ‘apply’ Function
Overview Swiftapply works on the pandas ‘apply’ function to make it efficient and quicker The package runs the apply operation is a vectorized style; …
Pandas will No Longer Support Python 2 Next Year
Overview Pandas will drop support for Python 2 from 1st January, 2019 This comes after Python’s core team announced they will stop support for …
Pandas on Ray – A Library to Make Pandas Faster with Just One Line of Code
Overview Pandas on Ray is a library that makes the Pandas library significantly faster It only requires just one line of code in the …
Perform Automated Feature Engineering in Python with Featuretools
Overview Feature Labs has launched a set to tools to make machine algorithms train quicker Automated feature engineering is at the heart of it …
Introductory guide to Linear Optimization in Python (with TED videos case study)
Introduction Data Science & Machine Learning are being used by organizations to solve a variety of business problems today. In order to create a …
Top 28 Cheat Sheets for Machine Learning, Data Science, Probability, SQL & Big Data
Introduction Data Science is an ever-growing field, there are numerous tools & techniques to remember. It is not possible for anyone to remember all …
Top 35 Articles and Resources from Analytics Vidhya for the year 2016
Introduction Reflection time! Yes – it is that time of the year, when you stand and look back. You take a small pause, soak …
16 New Must Watch Tutorials, Courses on Machine Learning
Introduction Most of us fail to acknowledge that Youtube has a massive resource center of machine learning tutorials which are free to access. You no longer …
Solutions for Skill test: Data Science in Python
Introduction Python is gaining ground very quickly among the data science community. We are increasingly moving to an ecosystem, where data scientists are comfortable …
