Learndataa Curriculum
The Learndataa Curriculum offers a structured, mentorship-based journey in data analytics and machine learning from beginner fundamentals to the mathematical foundations of AI. Developed and taught through 1-on-1 and small-group live sessions, these courses emphasize hands-on learning, clear reasoning, and real-world applications.All core content is freely available on YouTube for self-learners, with personalized mentorship available…
Webinar: What is Data Science, AI, ML?
Last day of registration: May 31, 2024 Register Online Hosted by:Dr. Nilesh Ingle, Ph.D. Freelancer, YouTuberFounder http://www.learndataa.comNagpur, IndiaAlumni North Carolina State University, Raleigh, NC, USAAlumni University University of North Carolina, Chapel Hill, NC, USAPostdoc Alumni, Virginia Tech, Blacksburg, VA, USAPostdoc Alumni, University of Minnesota, MN, USA Email: learndataa@gmail.com http://www.youtube.com/c/learndataa
Partial Least Squares (PLS-W2A algorithm)
Outline of the post: This post shows an implementation of the PLS-W2A algorithm from in Python using the source code from Scikit-learn docs. Partial Least Squares method can be used in datasets that have collinear features such as shown in figure above. [Check out videos: 1, 2, and project] References: (1) Jacob A. Wegelin. A…
Image Data Augmentation
Outline of the post: What is Image Data Augmentation? Image data of clouds and sun (hand drawn) Code to augment an image in Python What is Image Data Augmentation? Image data augmentation is a technique to create copies of altered original images. Thus increase the amount of data to train a model. This additional data…
Data Preprocessing: Whitening or Sphering in Python
Outline of the post: What is Whitening or Sphering? Why? Steps to Whiten a dataset Mathematical intuition Implementation of Whitening in Python What is Whitening or Sphering? Why? “A whitening transformation or sphering transformation is a linear transformation that transforms a vector of random variables with a known covariance matrix into a set of new variables whose covariance is the identity matrix, meaning that they are uncorrelated and…
Standardize a dataset. When and why?
Standardization is done to bring features of vastly different magnitudes into a similar range. In this post you will learn: When to standardize a data set for machine learning? How to use Scikit-learn’s preprocessing tools: .scale() .StandardScaler() Introduction “Standardization of datasets is a common requirement for many machine learning estimators implemented in scikit-learn.” – Scikit-learn Distance based machine…
Data in our lives
There is 40 zettabytes or 40 trillion gigabytes of data in the world today, year 2020! The volume of data is increasing at a faster rate than ever before. We create 2.5 quintillion bytes of data each day1 !!! i.e. equivalent of 2.5 million billion 1 terabyte hard drives. The world internet population has increased…
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