Day111 - STAT Review: Data & Sampling Distributions (1)
Practical Statistics for Data Scientists: Sampling, Bias, and Sampling Distribution(Central Limit Theorem)
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Day110 - STAT Review: Exploratory Data Analysis (2)
Practical Statistics for Data Scientists: Data Distribution, Correlation, and Various Data Visualization Plots
Day109 - STAT Review: Exploratory Data Analysis (1)
Practical Statistics of Data Scientists: Elements of Statistical Terminologies- Data Statistics Fundamentals, Data Types, and Estimates of Location & Var...
Continuing the TIL Project in 2025
The Ongoing Chronicles of TIL25 — A Motivating Expedition as a Data Scientist & AI/ML Engineer Candidate
Day108 Deep Learning Lecture Review - Advanced Techniques in DL
HW5: Out-of-distribution (OOD) Detection (Maximum Softmax Probability & ODIN) and Continual Learning (SLDA & IID Streaming)
Day107 Deep Learning Lecture Review - HW4 - Adjusting Probabilities into Real-World
HW4: Model Calibration (Platt Scaling & Label Smoothing) and Conformal Prediction (Naive and Adaptive Predictions Sets)
Day106 Deep Learning Lecture Review- Enhancing DL Workflows (Data Distribution)
HW3: Optimization through Data Loading, Profiling, & Scaling, and Comparison of Data Parallel & Distributed Data Parallel
Day105 Deep Learning Lecture Review - Lecture 20 (End)
Model Drifting, Periodic Re-Training, Detecting Model Drift, Continual Learning (Pre-Trained Model, NCC), and Real-Time Machine Learning
Day104 Deep Learning Lecture Review - Lecture 19
Data-Centric AI: Label Noise, Selection Bias, Data Leakage, and Error Analysis for Model Improvement (Subgroup Errors)
Day103 Deep Learning Lecture Review - Lecture 18 (2)
Data-Centric AI: Active Learning, SEALS(Similarity Search for Efficient Active Learning), Dataset Pruning, and Data Engine