Queries-Solved

3rd April 2019

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• What exactly is meant by shared weights in convolutional neural network?

• ⛔ How do I train weights of filters in convolutional layers in Convolutional Neural Network?

• ⛔ The reason behind moving in the direction opposite to the Gradient

• What is translation invariance in computer vision and convolutional neural network?

• What is activation in convolutional neural networks?

• How is a convolutional neural network able to learn invariant features?

4th April 2019

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• A Conceptual Explanation of Bayesian Hyperparameter Optimization for Machine Learning

GOOGLE SEARCH: bayesian optimization machine learning

• Understanding Hyperparameters and its Optimisation techniques

GOOGLE SEARCH: hyperparameter optimization techniques

• Dimensionality Reduction w/ Neural Nets

GoOGLE SEARCH: dimension reduction using hidden layers

• AI Ethics Resources
• Preventing Machine Learning Bias

types of bias in machine learning

⛔ ⛔ ⛔ ⛔ ⛔ ⛔ ⛔

✔️ The 25 Best Data Science and Machine Learning GitHub Repositories from 2018

✔️ 11 most read Deep Learning Articles from Analytics Vidhya in 2017

✔️ Introducing BodyPix: Real-time Person Segmentation in the Browser with TensorFlow.js

Papers 📃

📃 DROPOUT

5th April 2019

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✔️ How to Prepare for a Machine Learning Interview

Image Segmentation

✔️ Computer Vision Tutorial: A Step-by-Step Introduction to Image Segmentation Techniques(Part-1)

✔️ Image Segmentation using Python’s scikit-image module.

Interview

✔️ 12 Frequently Asked Questions on Deep Learning (with their answers)!

✔️ The Most Comprehensive Data Science & Machine Learning Interview Guide You’ll Ever Need

✔️ Ace Data Science Interview

8th April 2019

✔️ Feature Selection with sklearn and Pandas

✔️ Introduction to Feature Selection methods with an example (or how to select the right variables?)

✔️ Your Guide to Master Hypothesis Testing in Statistics

✔️ Understanding The Central Limit Theorem

✔️ P-Value , Significant level , Hypothesis testing

• Hypothesis Testing in Machine Learning

• Feature Selection for Categorical Variables

9th April 2019

✔️ Linear Discriminant Analysis for Machine Learning

✔️ Ways to Detect and Remove the Outliers

10th April 2019

• 6 Common Probability Distributions every data science professional should know

13th April 2019

Dimenstion reduction

✔️ Practical Guide to Principal Component Analysis (PCA) in R & Python

Introduction to Online Machine Learning: Simplified

The Ultimate Guide to 12 Dimensionality Reduction Techniques (with Python codes)

Online Learning Guide with Text Classification using Vowpal Wabbit (VW)

✔️ What is the difference between t-score, z-score and F-score?

14th April 2019

Statistical Blogs

✔️ A simple explanation to understand Chi-Square Test Go to the profile of Wenyi YAN

✔️ Importance of Distance Metrics in Machine Learning Modelling

✔️ Understanding AUC - ROC Curve | Video | [StackOverflow]

✔️ SMOTE implementation in Python

• An Introduction to Independent Component Analysis: InfoMax and FastICA algorithms | [Video]

Mathematics

• A comprehensive beginners guide to Linear Algebra for Data Scientists

19th April 2019

Statistics

✔️ Machine Learning: Unsupervised Learning — Feature Transformation

20th April 2019

✔️ Invisibility Cloak using Color Detection and Segmentation with OpenCV

21th April 2019

CONFIG

✔️ How to use ConfigParser in Python | [VIDEO]

22nd April 2019

Pooling

✔️ A Gentle Introduction to Pooling Layers for Convolutional Neural Networks

23rd April 2019

✔️ 6 Common Probability Distributions every data science professional should know

✔️ Basics of Probability for Data Science explained with examples

[] What is the difference and relationship between the binomial and Bernoulli distributions?

25th April 2019

Ensemble

✔️ A Comprehensive Guide to Ensemble Learning (with Python codes)

✔️ Essentials of Machine Learning Algorithms (with Python and R Codes)

Online Learning

[ ] Data Streams and Online Machine Learning in Python

26th April 2019

Object tracking

✔️ Object Tracking

29th April 2019

Support Vector Machine

✔️ A Quick Guide to Boosting in ML

• [] Curse of Dimensionality

• [] Support Vector Machine: Complete Theory of Support Vectors

• [] Support Vector Machine: Kernel Trick; Mercer’s Theorem

30th April 2019

Boosting

✔️ Complete Guide to Parameter Tuning in Gradient Boosting (GBM) in Python

[x] Complete Guide to Parameter Tuning in XGBoost (with codes in Python)

1st May 2019

DBSCAN

✔️ How DBSCAN works and why should we use it?

DATA SCIENCE WORKFLOW

✔️ 3 Tips to Improving Your Data Science Workflow

✔️ What is the workflow or process of a data scientist? What tools do they use?

✔️ Creating Interactive Animation for Parameter Optimisation using Plot.ly

✔️ The Simplest & Cleanest Method for Tracking a For Loop’s Progress and Expected Run Time in Python Notebooks

2nd May 2019

Object Tracking

✔️ Ball Tracking with OpenCV

3rd May 2019

Hu Moments

✔️ Shape Matching using Hu Moments

4th May 2019

OverDue

• OpenCV Track Object Movement
• OpenCV Face Recognition
• Liveness Detection with OpenCV
• The 5 Clustering Algorithms Data Scientists Need to Know

6th May 2019

Bag of words

Implementing Bag of Visual words for Object Recognition Object detection with neural networks — a simple tutorial using keras A gentle guide to deep learning object detection

10th May 2019

Research Paper

Getting started with reading Deep Learning Research papers: The Why and the How

Machine Learning

Machine Learning Interview Questions – Q4 – Explain how a ROC curve works

13th May 2019 ⭐ ⭐

Hypothesis Testing

✔️ Understanding Hypothesis Tests: Significance Levels (Alpha) and P values in Statistics

Confusion Matrix

✔️ Accuracy, Recall, Precision, F-Score & Specificity, which to optimize on?

15th May 2019

⭐ interview questions

• Statistics: given a random sample (size n) drawn from a uniform distribution [0, d], how can we estimate d?

• Given n samples from a uniform distribution [0, d], how to estimate d?

• Confidence Interval for maximum

18th May 2019

R^2

• WHY IS INTERCEPT IMPORTANT IN REGRESSION ANALYSIS?

P-value vs Alpha

• What is the difference between an alpha level and a p-value?

21th May 2019

Decision Tree

• The Complete Guide to Decision Trees

Auto Encoders

• Auto-Encoder: What Is It? And What Is It Used For? (Part 1)

22nd May 2019

Data Mining

✔️ An Introduction to Data Mining

✔️ What is Data mining

Decision Tree

✔️ Classification and Regression Analysis with Decision Trees

24th May 2019

XGBOOST

⭐ How exactly XGBoost Works?

⭐ An End-to-End Guide to Understand the Math behind XGBoost

⭐ ENTROPY

⭐ ⭐ what-is-entropy-and-why-information-gain-is-matter

25th May 2019

⭐ ⭐ ASSOSIATION RULE

✔️ Complete guide to Association Rules (1/2)

Pytorch CUda

✔️ Speed Up your Algorithms Part 1 — PyTorch

⭐ ⭐ Noise in DATA

✔️ How to use Noise to your advantage ?

26th May 2019

⭐ ⭐ IMAGE PROCESSING

✔️ Image Pre-processing

29th May 2019

Image Classification

✔️ Image Classification with Convolutional Neural Networks

30th May 2019

Support Vector Machine

✔️ Chapter 2 : SVM (Support Vector Machine) — Theory

✔️ Chapter 2 : SVM (Support Vector Machine) — Coding