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Machine Learning Part 11 - Feature Selection

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December 10, 2020

Machine Learning Part 11 - Feature Selection

Feature Selection

Bite Sized Learning

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Bite Sized Learning: Printing Patterns

June 20, 2020

Bite Sized Learning - Prining Patterns This will be handy when you attend interviews or exams Refer the code file for various patterns using numbers, alphabets and characters - Patterns

Bite Sized Learning - Data Visualization Basics in Python - Matplotlib

May 17, 2020

Data Visualization Basics in Python - Matplotlib Data visualization is the graphical representation of data. It helps to understand complex relationship between data by simplying it. Visuals tell story. Click below link to see sample codes Matplotlib Some common charts and its description Reference: https://pythonawesome.com/

Bite Sized Learning: Data Preparation

August 07, 2020

Importance of Data Preparation & Common Methods Data preparation is the various methods and steps taken to transform the data such that it is suitable for ML algorithms. Here quality precedes over quantity. Hence it is essential to transform the raw data into to a more informative format for a better modelling task. Below are the most commonly followed data preparation tasks in data science industry Data Cleaning Feature Engineering Data Transformation Feature Extraction Data Cleaning: Data cleaning is the process of detecting and also treating inaccurate data points from a data set. This is the most time consuming and critical part of ML. It simply goes "garbage in = garbage out". Below are some of the methods to clean data Find the number / percentage (both) of missing rows or null values (NAN) & treat it Identify the duplicate rows within the dataset & treat it Detect the outliers using statistics & treat it using doma...

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Arockia Liborious: Arockia Liborious is a visionary in the field of artificial intelligence and analytics, known for his groundbreaking work in leveraging machine learning to catalyze innovation and operational efficiency across the banking, manufacturing, and service sectors worldwide. With a rich career spanning over 15 years, Arockia stands at the forefront of integrating AI technologies to enhance customer experiences, streamline operations, and foster strategic growth. Celebrated as a Top 25 Thought Leader in Predictive Analytics by Thinkers360, his influence extends through his prolific contributions to the field, including his role as an esteemed author and speaker. His strategic involvement on the board of advisors for various non-profit AI and ML forums underscores his commitment to advancing the industry through collaborative knowledge sharing and mentorship. Arockia's work, characterized by a deep technical prowess and visionary leadership, not only sets industry benchmarks but also inspires the next generation of data scientists and AI innovators.

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Data Science

Machine Learning Part 11 - Feature Selection

Machine Learning Part 11 - Feature Selection

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Bite Sized Learning: Printing Patterns

Bite Sized Learning - Data Visualization Basics in Python - Matplotlib

Bite Sized Learning: Data Preparation