R - Getting Started
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Blog posts
2022
Multivariate Visualization
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This post covers Multivariate Visualization.
Bivariate Visualization
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This post covers Bivariate Visualization.
Univariate Visualization
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This post covers Univariate Data Visualization.
Data Assessing and Cleaning
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This post covers Data Assessing and Cleaning.
Data Gathering
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This post covers Data Gathering.
Data Wrangling
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This post covers Data Wrangling.
Python - Pandas
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This post covers Introduction to Pandas.
Outliers
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This post covers detecting outliers.
Python - Introduction
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This post covers Introduction to Python Programming.
Python - Getting Started
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Download Python.
2021
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Tableau - Forecasting
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This post covers Forecasting.
Tableau - Trend Lines
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This post covers Trend Lines.
Tableau - Geo Map
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This post covers geo maps.
Tableau - Calculated Field
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This post covers Calculated Field.
Tableau - Data Aggregation
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This post covers Data Aggregation.
Tableau - Filtering and Sorting
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This post covers Filtering and Sorting
Tableau - Visualization - Introduction
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This post covers visualization.
Tableau - Connecting to Data
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Connecting to Data
Tableau - Dashboard and Stories
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This post covers Dashboard and Stories.
Tableau - Getting Started
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Download
Introduction to adversarial robustness
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This lesson is from Adversarial Robustness - Theory and Practice
Help Cmd
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This lesson is for help.
Digital Transformation
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This lesson covers Agile Methodology from TutorialsPoint
Digital Transformation
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This post covers Agile Transformational Practices (from Driving Digital Transformation, by Isaac Sacolick, AMACOM)
Critical Factors
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This lesson is from Digital Transformation Handbook by John Palfreyman.
Blockchain
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This lesson is from Blockchain
Cloud Computing
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This lesson is from Intro to Cloud Computing
Mobile Computing
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This lesson is from Mobile Computing
Reality Technologies
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This lesson is from Virtual Reality, Augmented Reality, and Mixed Reality, Augmented, Virtual, and Mixed Reality, and Mixed Reality.
Internet of Things
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This lesson is from Tutorialspoint.
Big Data
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This lesson is from Wikipedia and Courseera course by BCG & University of Virginia
Digital Transformation
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This lesson is from Digital Transformation by Indian School of Business.
Digital Transformation
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This lesson is from Digital Transformation by Indian School of Business.
Digital Transformation
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This lesson is from Digital Transformation by Indian School of Business.
Digital Transformation
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This lesson is from Digital Transformation by BCG & University of Virginia
Digital Transformation
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This lesson is from Digital Transformation Handbook by John Palfreyman
Digital Transformation
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This lesson is from Digital Transformation Handbook by John Palfreyman
Digital Transformation
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This lesson is from Digital Transformation Handbook by John Palfreyman
Digital Transformation
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This post covers phases of the digital transformation (from Industrial Digital Transformation, by Shyam Varan Nath, Ann Dunkin, Mahesh Chowdhary, Nital Patel - Packt Publishing)
Digital Transformation
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This lesson covers Industrial revolution (from Industrial Digital Transformation, by Shyam Varan Nath, Ann Dunkin, Mahesh Chowdhary, Nital Patel - Packt Publishing) and Digital Transformation Handbook by John Palfreyman.
Digital Transformation
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This post covers introduction to digital transformation (from Thomas M. Siebel).
Digital Transformation
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This lesson is from Digital Transformation Handbook by John Palfreyman
Variance and Standard Deviation
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This lesson covers Variance and Standard Deviation.
Range and Quartiles
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This lesson covers Range and Quartiles.
Skewed Distribution
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This lesson covers Introduction to Skewed Distribution.
Linear Regression
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This lesson covers Linear Regression.
Building AI
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This lesson is from AI For Everyone
Artificial Intelligence
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This lesson is from AI For Everyone
Deep Learning Book
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Introduction
Natural Adversarial Examples
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This post covers paper Natural Adversarial Examples
Explaining and Harnessing Adversarial Examples
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This post covers paper “Explaining and Harnessing Adversarial Examples”
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey
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This post covers paper “Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey”
Fast Gradient Sign Attack
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This post covers MNIST implementation of ICLR 2015 paper “Explaining and Harnessing Adversarial Examples”
Towards General Purpose Vision Systems
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This post covers paper “Towards General Purpose Vision Systems”
Chi-square
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This post explains Chi-square Test.
t Table
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This post provides t Table.
Hyothesis
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This post covers Hypothesis Testing.
Estimation
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This post covers Estimation.
Slides
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This post explains creating slides using Jupyter Notebook.
Sampling Distributions Example
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This post covers Sampling Distributions Example.
Logical and Physical Markups
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This post covers introduction to Logical and Physical Markups.
Form Validation
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This lesson covers Client-side form validation.
Filter Elements
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This lesson covers Filtering HTML Elemens.
Document Object Model
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This lesson covers Document Object Model (DOM).
Probability Distributions
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This post covers Probability Distributions.
Normal Distribution
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This post covers Normal Distribution.
Z Table
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This post provides Z Table.
Functional Programming
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This lesson covers JavaScript Functional Programming.
JavaScript Fundamentals
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This lesson covers JavaScript Fundamentals.
Sampling Distributions
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This post covers Sampling Distributions.
What is being transferred in transfer learning
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This post covers paper “What is being transferred in transfer learning” by Google / Google Brain (NeurIPS 2020).
JavaScript Fundamentals
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This lesson covers JavaScript Lab Fundamentals.
MySQL - Getting Started
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This post covers installation of MySQL.
Flask-Cookie-Session
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This post covers Cookie and Session in Flask.
Flask-Profile
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This post covers user profile management system using MySQL.
Flask-Cookie
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This post covers cookie in Flask!
Flask
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This post covers forms in Flask using Calculator App!
Flask
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This post covers introduction to Flask!
Projects
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This post covers projects covered by Students.
Machine Learning
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This lesson is on Machine Learning notes.
Introduction to Deep Learning
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This post covers introduction to Image Classification using Deep Learning.
Notes on CNN - Data and Loss
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This post covers CNN Architecture from cs231n.
Notes on CNN - Architecture
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This post covers CNN Architecture from cs231n.
Notes on Optimization
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This post covers Optimization and Backpropogation from cs231n.
Notes on Optimization
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This post covers Optimization and Gradient Descent from cs231n.
Image Classification
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This post covers image classification, nearest neighbor classifier, k-nearest neighbor classifier and validation sets from cs231n.
Mean Median Mode
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This post covers Introduction to descriptive statistics.
Descriptive Statistics
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This lesson is from Introduction to Descriptive Statistics by Jackie Nicholas, Mathematics Learning Centre, University of Sydney
Python-Libraries
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This post covers Introduction to some other python libraries.
MNIST-NN
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This post covers introduction to Neural Network using MNIST dataset.
MNIST-CNN
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This post covers introduction to Convolution Neural Network using MNIST dataset.
HTML Forms
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This post covers introduction to HTML Forms.
2020
HTML Fundamentals
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This lesson covers HTML Fundamentals.
CSS Fundamentals
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This lesson covers CSS Fundamentals
Maths and Statistics
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This post covers certain formulas useful for Deep Learning.