How to write a short summary on a Topic ?

Forget what you have written, Evaluate your answer/perspective

• What is the takeaway you want for the reader
• What points will create interest
• What 2-3 Buzzwords in it will create curiosity

Keep connecting to your readers!!!

Focus / Being Aligned

• Follow through, Don't miss look at big picture
• Fence your focus, weed your distraction
• Cycle around your focus, keep learning, incremental additions
• Discuss concerns / issues
• Keep passion / interests always focused

Keep Exploring!!!

Being ahead of Learning curve

• Keep a connecting line for every new concept / idea to the past lessons
• Cycle the subject, again and again, Learning needs iterations
• Awareness - Code - Practice - Do Often
• Aware of trends / Competitors
• Provide insights / inference / observations

Tech is interesting, Keep Exploring!!!

OpenCV Notes

Color channels

• Hue: Measures the color of the pixel.
• Saturation: Measures the intensity of color of the pixel.
• Value: Measures the brighness of the pixel.

Hue range

• Red (0-60)
• Yellow (60-120)
• Green (120-180)
• Cyan (180-240)
• Blue (240-300)
• Magenta (300-360)

RGB Channels

• (0,0,0) is a black color.
• (255,0,0) is a pure red color.
• (0,255,0) is a pure green color.

 

Smoothing Functions

• Image Smoothing - convolving the image with a low-pass filter kernel. It is useful for removing noise
• Bilateral filter - replaces the intensity of each pixel with a weighted average of intensity values. cv.bilateralFilter() is highly effective in noise removal while keeping edges sharp

Color Codes

Mask for custom color range

Keep Thinking!!!!

Myth of Data

•  I don't like my job
• Data is insufficient
• There are no good data science use cases

Learn all coding questions, Practice and learn all ML maths, Solve all kaggle problems, Land your dream job, the data you will face the same problem

• Data is insufficient

What you see in learning / kaggle is not real-world data issues

Wherever you go, bad data and incomplete data only will be there. 

Keep Thinking!!!

Recommendation Systems

Bookmark of Repos for my ongoing learning

Deep Learning based Recommender System: A Survey and New Perspectives

• recmetrics - A python library of evalulation metrics and diagnostic tools for recommender systems.
• List of Recommender Systems
• Case Recommender - A Python Framework for RecSys
• Implicit
• Recommenders - Microsoft
• Recommender Systems in Python 101
• LightFM is a Python implementation of a number of popular recommendation algorithm
• Spotlight uses PyTorch to build both deep and shallow recommender models
• Build a Recommendation Engine With Collaborative Filtering
• Crab - Recommender systems in Python
• Beginner Tutorial: Recommender Systems in Python
• Recommendation System in Python
• Surprise is a Python scikit for building and analyzing recommender systems that deal with explicit rating data.

High level thoughts

• Data connectors class
• SVDclass - Dataload - Algorun - Validate - Results
• NMFclass - Dataload - Algorun - Validate - Results
• ItemItemrecomclass - Dataload - Algorun - Validate - Results
• UserUserrecomclass - Dataload - Algorun - Validate - Results

Structuring Your Project

Keras Reads

• Building a book Recommendation System using Keras
• keras-recommender
• Deep Beers: Playing with Deep Recommendation Engines Using Keras
• A Transformer-based recommendation system
• Collaborative Filtering for Movie Recommendations
• Memory-efficient embeddings for recommendation systems

July 5th Updates

Building and comparing recommendation systems to scale using scikit-surprise (surprise library)

Sampling Methods to speed up Clustering Algorithms

Recommender System - matrix factorization algorithm.

Recommendation system with Python using Movie Lens Data Set.

Softmax DNN for Recommendation

Colab: Build a Movie Recommendation System

Collaborative Filtering

Matrix Factorization 

A Recurrent Neural Network Based Recommendation System

Keep Thinking!!!!

Text to Image generation

min(DALL·E)

Sample input

Output

DALL·E Mini

paper - Zero-Shot Text-to-Image Generation

Colab

A quick thread on "How DALL-E 2, Imagen and Parti Architectures Differ" with breakdown into comparable modules, annotated with size 🧵#dalle2 #imagen #parti

* figures taken from corresponding papers with slight modification
* parts used for training only are greyed out pic.twitter.com/9zsIUq3toU

— Rosanne Liu (@savvyRL) June 25, 2022

Keep Exploring!!! 

Personalized - Redefined - Recommendations - Paid Service

What if we get a customized recommendation based on our needs than based on what we are forced to see. 

Workday recommendations (Articles / Videos based on interests)

• Data Science (20%)
• Startups (20%)
• Stock markets (20%)
• Travel Vlog (10%)
• Paranormal Vlog (5%)
• Food Vlog(5%)
• Emotions / Wellness (10%)

Weekend Recommendations

• Travel Vlog (20%)
• Paranormal Vlog (20%)
• Food Vlog(10%)
• Emotions / Wellness (20%)
• Music (30%)

Tired of seeing the same swiggy ads, zomato ads, irrelevant to the context ads.

Ref - Link

Keep Thinking!!!

Targeted Advertising - Kids - Personalization vs Privacy vs Kids

When we shop/buys/browse our online footprint leaves us with #targetedads. For kids via #Edtech Products - Kids data collection - Third-party targeted advertising for kids :(

Online Education vs Privacy vs Personalization vs Family Recommendations vs Where do you draw the line of privacy. 

Detailed Analysis - Link

• Of the 163 EdTech products reviewed
• Trailed children outside of their virtual classrooms and across the internet, over time
• Most online learning platforms sent or granted access to children’s data to third-party companies, usually advertising technology (AdTech) companies

We need to #spare kids from the targeted advertising

We think our kids are safe in school online. But many are being surveilled 🔍, and often parents and teachers have been kept in the dark. Kids are priceless, not products. #StudentsNotProducts #dataprivacy https://t.co/X0qwtQDQkG pic.twitter.com/SGk7I1m62c

— Human Rights Watch (@hrw) May 25, 2022

Keep Thinking!!! 

Retail - Vision Offerings

 

Ref - Link

Few more companies - vue.ai, orbo.ai and custom AI offerings for fashion, beauty.

Keep Exploring!!!