2021

05-13 One Powerful Question
05-09 Working with R
05-06 Data Manipulation in R - Book Review
05-05 A Foreign Exchange Primer
05-03 Mathematical Statistics with Resampling and R
05-02 Quote for the day
05-01 Blah Blah Blah - Book Review
04-24 Quote for the day
04-23 Introduction to Statistical Learning - Revisit
04-22 ESG Investments: Filtering vs. ML
04-19 Mathematical Notation - Book Review
04-15 The Formula - Book Summary
04-10 You Look Like a Thing and I Love You - Summary
04-10 Hiatus

2020

11-12 Python Tricks - A Buffet of Awesome Python Features
11-06 You Look Like a Thing and I Love You
08-14 Treading on Python - II - Book Summary
08-12 Tiny Python Projects - Book Summary
08-11 Python Testing 101 and Testing 201 with pytest
08-04 Python Workout - Book Summary
07-06 Conversations with Hugging Face CTO
07-05 Super Mario Effect for Learning
06-22 Attention is all you need
06-10 Transformer Primer : Jay Allamar
06-10 BERT Neural Network Explained, Transformers
06-10 Attention Primer : Jay Allamar
03-18 Information Theory Book Review
03-15 Machine Learning for Business Using Amazon SageMaker and Jupyter
02-08 A Big Data Hadoop and Spark project for absolute beginners

2019

11-26 O’Reilly Datashow: Apache Spark Journey from Academia to Industry
11-25 Data Science makes an impact on Wall Street
11-24 Maching Learning for Indexing
11-02 Ian GoodFellow Interview
11-01 Bert Limitations
10-19 Indistractable - Book Summary
10-12 My Learnings from attending PyCon SG19 Tutorial on Deep Learning
10-12 Multiprocessing vs. Threading in Python: What Every Data Scientist Needs to Know
09-26 Data Leakage
09-25 MASE
09-25 Forecasting time series using R by Prof Rob J Hyndman
09-18 Using Transfer Learning and Pre-trained Language Models to Classify Spam
09-18 Embeddings in NLP and beyond
09-18 BERT
09-13 LSTM Models for Simulated Time Series data
09-13 Heuristics
09-12 Early Stopping in Keras
09-11 Generative LSTM
09-10 Stacked LSTM
09-10 Sequence to Sequence LSTM
09-10 Plain Vanilla LSTM