365 Days of Data
A year-long journey with data science, AI, machine learning, and deep learning.
Projects Completed
| Projects | Description | Deployment |
|---|---|---|
| Football Players Market Value Prediction | A 10-day end-to-end machine learning capstone project involving data scraping, cleaning, feature engineering, model training, and deployment. Achieved 94% accuracy using gradient boosting algorithms. | Live Demo 👆🏽 |
| Movie Recommender System | An end-to-end content-based movie recommender system leveraging a dataset of 5000 movies from Kaggle. Built with cosine similarity and TF-IDF vectorization. | Live Demo 👆🏽 |
| Cat vs Dog Classifier | A deep learning model leveraging VGG16 architecture, trained on an RTX 3050 Ti for 30 epochs, achieving 95% accuracy using the Kaggle Dogs vs Cats dataset. | Live Demo 👆🏽 |
| Guess The Footballer By Eyes | An interactive game where users compete against AI to recognize 25 famous footballers by their eyes alone. Built with ResNet18 achieving 70% accuracy. Features scoring system and streak tracking. | Demo 👆🏽 |
| Seq2Seq Chatbot | A sequence-to-sequence chatbot trained on Cornell Movie-Dialogs Corpus using encoder-decoder architecture with Luong attention mechanism. Built from scratch in PyTorch. | Live Demo 👆🏽 |
| GPT from Scratch | Complete implementation of GPT transformer architecture from scratch following Karpathy’s tutorial. Includes bigram model, self-attention, multi-head attention, and complete transformer blocks. | Notebook 📓 |
| Image Captioning | An end-to-end image captioning project using the Flickr8k dataset. Explored the “Show, Attend & Tell” paper, built vocabulary, extracted features with ResNet-18, and trained a transformer decoder. Achieved a BLEU-4 score of 0.18 and deployed a Streamlit demo app. | Live Demo 👆🏽 |
| cineRank - A movie ranker app | Community-driven movie leaderboard app with trending picks, sentiment reviews, and personal watchlists. Built using IMDb reviews, advanced text cleaning, EDA, vectorization (BoW, TF-IDF, GloVe, BERT), and BERT fine-tuning for sentiment classification. Features leaderboard, watchlists, and real-time updates. | Live Demo 👆🏽 |
| Choose Your Own Adventure | Inspired by interactive fiction like AI Dungeon, this app lets you become the protagonist in a personalized adventure story. Enter any theme—haunted mansions, space exploration, and more—and AI generates a unique branching narrative with multiple paths and endings. Features include an interactive visual map, concise story nodes (40 words), meaningful choices, and a clean black-and-white interface for all devices. Explore different decision paths and control your own dynamic storytelling experience. | Project Demo 👆🏽 |
| Projects-Based-GenAI | Hands-on GenAI projects including text generation, multimodal models, and advanced LLM fine-tuning. Explore practical implementations of state-of-the-art generative AI techniques. | Project folder |
| Project-Based-AgenticAI | Applied agentic AI projects focusing on autonomous agents, multi-agent systems, and real-world agentic workflows using LangGraph and LangChain. | Project folder |
Progress
| Days | Date | Topics | Resources | |
|---|---|---|---|---|
| Day1 | 2024‑12‑14 | Basics of Linear Algebra | 3blue1brown | |
| Day2 | 2024-12-15 | Decomposition, Derivation, Integration, and Gradient Descent | 3blue1brown | |
| Day3 | 2024-12-16 | Supervised Learning, Regression and classification | Machine Learning Specialization | |
| Day4 | 2024-12-17 | Unsupervised Learning: Clustering and dimensionality reduction | Machine Learning Specialization | |
| Day5 | 2024-12-18 | Univariate linear Regression | Machine Learning Specialization | |
| Day6 | 2024-12-19 | Cost Functions | Machine Learning Specialization | |
| Day7 | 2024-12-20 | Gradient Descent | CampusX, Machine Learning Specialization | |
| Day8 | 2024-12-21 | Effect of learning Rate, Cost function and Data on GD | CampusX, Machine Learning Specialization | |
| Day9 | 2024-12-22 | Linear Regression with multiple features, Vectorization | Machine Learning Specialization | |
| Day10 | 2024-12-23 | Feature Scaling, Visualization of Multiple Regression and Polynomial Regression | Machine Learning Specialization | |
| Day11 | 2024-12-24 | Feature Engineering, Polynomial Regression | Machine Learning Specialization | |
| Day12 | 2024-12-25 | Scikit-Learn revision, Linear Regression using Scikit Learn | Machine Learning Specialization | |
| Day13 | 2024-12-26 | LR lab, Classification | Machine Learning Specialization | |
| Day14 | 2024-12-27 | Logistic Regression, Sigmoid Function | Machine Learning Specialization , CampusX | |
| Day15 | 2024-12-28 | Decision Boundary, Cost Function | Machine Learning Specialization , CampusX | |
| Day16 | 2024-12-29 | Gradient Descent for logical regression | Machine Learning Specialization , CampusX | |
| Day17 | 2024-12-30 | Underfitting, Overfitting, Regularization Polynomial Features, Hyperparameters | Machine Learning Specialization | |
| Day18 | 2024-12-31 | Neurons, Neural Netowrk, Forward Propagation | Machine Learning Specialization | |
| Day19 | 2025-01-01 | Forward Propagation, Tensorflow implementations | Machine Learning Specialization | |
| Day20 | 2025-01-02 | Building and comparing models (Binary Classification) | Machine Learning Specialization | |
| Day21 | 2025-01-03 | Vectorization, Model training using Tensoflow | Machine Learning Specialization | |
| Day22 | 2025-01-04 | Activation Functions, Softmax Intution | Machine Learning Specialization | |
| Day23 | 2025-01-05 | Implementing Softmax | Machine Learning Specialization | |
| Day24 | 2025-01-06 | Backpropagaton, What and how?? | Machine Learning Specialization | |
| Day25 | 2025-01-07 | Backpropagation - Why? Advices for applying machine Learning | Machine Learning Specialization | |
| Day26 | 2025-01-08 | Model selection, training test, cross validation, Bias and Variance, Learning curves | Machine Learning Specialization | |
| Day27 | 2025-01-09 | Machine Learning Development Process, ML workflow | Machine Learning Specialization | |
| Day28 | 2025-01-10 | Implementing ML model: Error Analysis and Transfer Learning | Notebook: Implementation, Machine Learning Specialization | |
| Day29 | 2025-01-11 | Error Metrices, Encoding of Categorical Data, Transoformers | Machine Learning Specialization , CampusX | |
| Day30 | 2025-01-12 | Scikit-Learn Pipelines & Ridge Regression (L2 Regularization) | Documentation: Scikit-Learn , CampusX | |
| Day31 | 2025-01-13 | Lasso Regression (L1 Regularization), Elastic Net Regularization | ML playlist @CampusX | |
| Day32 | 2025-01-14 | Decision Tree Emtropy and Information Gain | ML playlist @CampusX | |
| Day33 | 2025-01-15 | Hyperparameters of Decision Tree with Scikit Learn, Regression Trees | ML playlist @CampusX , Visualize Yourself» | |
| Day34 | 2025-01-16 | Visualization Using DtreeViz(), Ensemble Learning | Github Repo: Dtreeviz, ML playlist @CampusX | |
| Day35 | 2025-01-17 | Voting Ensemble » Classification and Regression | ML playlist @CampusX , Visualize Yourself | |
| Day36 | 2025-01-18 | Bagging Ensemble > Classification and Regression | ML playlist @CampusX | |
| Day37 | 2025-01-19 | Random Forest: Intution, Working and difference with bagging, Random Forest Hyperparameters | ML playlist @CampusX | |
| Day38 | 2025-01-20 | Boosting Ensemble: Adaboost Boosting | ML playlist @CampusX | |
| Day39 | 2025-01-21 | Understanding GradientBoosting with Regression | ML playlist @CampusX | |
| Day40 | 2025-01-22 | Gradient Boosting with Classification | ML playlist @CampusX , Vlog Link | |
| Day41 | 2025-01-23 | XGboost Introduction | ML playlist @CampusX | |
| Day42 | 2025-01-24 | XGBoost for Regression and Classification, Catboost Vs XGboost Vs LightGBM | ML playlist @CampusX ,Research Paper | |
| Day43 | 2025-01-25 | Stacking Ensemble, Understanding Blending and K fold | ML playlist @CampusX | |
| Day44 | 2025-01-26 | K-Nearest Neighbor, Coding KNN from Scratch | ML playlist @CampusX | |
| Day45 | 2025-01-27 | Support Vector Machine | ML playlist @CampusX | |
| Day46 | 2025-01-28 | K-Means Clustering, DBSCAN | Notebook: K-Means clustering Demo , Notebook: DBSCAN demo | |
| Day47 | 2025-01-29 | Hierarchical Clustering, Silhouette Score | Kaggle, ML playlist @CampusX | |
| Day49 | 2025-01-30 | PCA (Principle Component Analysis), Implementing with MNIST dataset | Notebook: Applying PCA on MNIST dataset | |
| Day50 | 2025-02-01 | Visualizing and Comparing PCA, t-SNE, UMAP, and LDA + Revision with the course ML specialization | Machine Learning Specialization | |
| Day51 | 2025-02-02 | Anomaly Detection | Machine Learning Specialization, Notebook: Anomaly Detection | |
| Day52 | 2025-02-03 | Collaborative Filtering | Machine Learning Specialization | |
| Day53 | 2025-02-04 | Project @ Football Players Market Value Prediction - Introduction and Planning | Project Plan | |
| Day54 | 2025-02-05 | Project @ Football Players Market Value Prediction - Collecting Data (Scraping) | Notebook | |
| Day55 | 2025-02-06 | Project @ Football Players Market Value Prediction - Cleaning Data | Notebook | |
| Day56 | 2025-02-07 | Project @ Football Players Market Value Prediction - EDA | Notebook | |
| Day57 | 2025-02-08 | Project @ Football Players Market Value Prediction - Feature Engineering: (Creating features, Transforming Features) | Notebook | |
| Day58 | 2025-02-09 | Project @ Football Players Market Value Prediction - ML: (Linear Regression with Refined Features and deploying with Streamlit) | Notebook | |
| Day59 | 2025-02-10 | Project @ Complete Streamlit setup for Linear Regression | Streamlit Documentation | |
| Day60 | 2025-02-11 | Project @ Testing Ridge, Lasso, and Decision Trees | Project @ Football Players Market Value Prediction | |
| Day61 | 2025-02-12 | Project @ Had to hit reset from Feature Engineering | Project @ Football Players Market Value Prediction | |
| Day62 | 2025-02-13 | Project @ Finalizing Project and Deploying it | Project @ Football Players Market Value Prediction | |
| Day63 | 2025-02-14 | Content-Based Movie Recommender System - Preprocessing | Notebook | |
| Day64 | 2025-02-15 | Content-Based Movie Recommender System - Building and Deployment | Live Demo | |
| Day65 | 2025-02-16 | Diving into Deep Learning | Intro to Deep Learning @MIT | |
| Day66 | 2025-02-17 | Perceptrons | Deep learning playlist @ CampusX | |
| Day67 | 2025-02-18 | Perceptron, Loss function and gradient Descent | Deep learning playlist @ CampusX , Grokking Deep Learning @Andrew W. Trask | |
| Day68 | 2025-02-19 | Multilayer Perceptron | Deep learning playlist @ CampusX | |
| Day69 | 2025-02-20 | MLP notation, Forward Propagation | Deep learning playlist @ CampusX | |
| Day70 | 2025-02-21 | Loss Functions for deep learning | Deep learning playlist @ CampusX | |
| Day71 | 2025-02-22 | Backpropagation, deep diving this time | Deep learning playlist @ CampusX | |
| Day72 | 2025-02-23 | Implementing Backpropagation for Regression | Notebook: Backpropagation Regression | |
| Day73 | 2025-02-24 | Implementing Backpropagation for Classification | Notebook: Implementation Backprop Classification | |
| Day74 | 2025-02-25 | Revising old days, Memoization | Deep learning playlist @ CampusX | |
| Day75 | 2025-02-26 | Vanishing Gradient, Exploding Gradient | Deep learning playlist @ CampusX | |
| Day76 | 2025-02-27 | Implementing artificial neural networks (ann) for different datasets | Deep learning playlist @ CampusX | |
| Day77 | 2025-02-28 | Improving Neural Networks | Deep learning playlist @ CampusX | |
| Day78 | 2025-03-01 | Sequence Modeling / RNNs - Just Overview | Intro to Deep Learning @MIT | |
| Day79 | 2025-03-02 | Transformers Attention - Just Overview | Intro to Deep Learning @MIT | |
| Day80 | 2025-03-03 | CNNs - Just Overview Part 1 | Intro to Deep Learning @MIT | |
| Day81 | 2025-03-04 | CNNs - Just Overview Part 2 | Intro to Deep Learning @MIT | |
| Day82 | 2025-03-05 | Deep Generative Modeling - Just Overview | Intro to Deep Learning @MIT | |
| Day83 | 2025-03-06 | Reinforcement Learning - Just Overview | Intro to Deep Learning @MIT | |
| Day84 | 2025-03-07 | Deep Learning: Challenges & New Frontiers - Just Overview | Intro to Deep Learning @MIT | |
| Day85 | 2025-03-08 | Early Stopping & Normalizing Inputs, Droput | Deep learning playlist @ CampusX, Grokking Deep Learning @Andrew W. Trask | |
| Day86 | 2025-03-09 | Regularization, Quantization | Deep learning playlist @ CampusX | |
| Day87 | 2025-03-10 | Activation Functions - Revisited | Deep learning playlist @ CampusX | |
| Day88 | 2025-03-11 | Weight Initialization | Deep learning playlist @ CampusX | |
| Day89 | 2025-03-12 | Deep Learning Optimizers | Deep learning playlist @ CampusX | |
| Day90 | 2025-03-13 | Keras Tuner | Deep learning playlist @ CampusX | |
| Day91 | 2025-03-14 | Deep Diving into CNNs | Deep learning playlist @ CampusX | |
| Day92 | 2025-03-15 | Understanding Paddings and Strides | Deep learning playlist @ CampusX | |
| Day93 | 2025-03-16 | Backpropagation in CNNs: A Quick Breakdown | Deep learning playlist @ CampusX, Grokking Deep Learning @Andrew W. Trask | |
| Day94 | 2025-03-17 | LeNet5, Cat Vs Dog Classification | Deep learning playlist @ CampusX, Grokking Deep Learning @Andrew W. Trask | |
| Day95 | 2025-03-18 | GPU slow than CPU - well in my case? | Deep learning playlist @ CampusX | |
| Day96 | 2025-03-19 | Data Augmentation, Pretrained Models | Deep learning playlist @ CampusX, Grokking Deep Learning @Andrew W. Trask | |
| Day97 | 2025-03-20 | Visualizing Convolutional Layers, Transfer Learning | Deep learning playlist @ CampusX, Grokking Deep Learning @Andrew W. Trask | |
| Day98 | 2025-03-21 | Keras Functional API | Deep learning playlist @ CampusX , Article | |
| Day99 | 2025-03-21 | Finalizing Dog Cat Classifier Project | Project - Live Demo | |
| Day100 | 2025-03-23 | Hidden Markov Model, Quantum Machine Learning | Medium Article: Understanding Hidden Markov Models | |
| Day101 | 2025-03-24 | Exploring Pytorch Surfacely | DL with Pytorch - Datacamp | |
| Day102 | 2025-03-25 | Training a neural network with pytorch | DL with Pytorch - Datacamp | |
| Day103 | 2025-03-26 | Evaluating and improving models | DL with Pytorch - Datacamp | |
| Day104 | 2025-03-27 | Crawling through DL with pytroch | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day105 | 2025-03-28 | Starting chapter 2 : from model to production | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day106 | 2025-03-29 | Exploring Autograd and Portfolio Tweaks | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day107 | 2025-03-30 | Refining Portfolio whole day | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day108 | 2025-03-31 | Autograd in PyTorch: Deeper Understanding | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day109 | 2025-04-01 | PyTorch Training Pipeline (Manual + Using nn.Module) | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day110 | 2025-04-02 | Dataset & DataLoader Class in PyTorch | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day111 | 2025-04-03 | ANN on Fashion MNIST, GELU | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day112 | 2025-04-04 | ANN on larger FMNIST dataset with GPU (local), GELU/SiLU history | Deep Learning for Coders -Fast.Ai, @CampusX | |
| Day113 | 2025-04-05 | Optimizing FMNIST NN using Dropouts, Regularization and Batch Normalization in Pytorch | Notebook | |
| Day114 | 2025-04-08 | RNNs revisited, Karpathy’s blog, Project Planning | Karpathy Blog | |
| Day115 | 2025-07-08 | Classifying Footballers with their Eyes - Day 1 | Project Notebook | |
| Day116 | 2025-07-09 | Classifying Footballers with their Eyes – Day 2 | Project Notebook | |
| Day117 | 2025-07-10 | YOLO (You Only Look Once) | YOLO Paper | |
| Day118 | 2025-07-11 | LSTM, GRU & Encoder-Decoder Architecture | Colah’s Blog | |
| Day119 | 2025-07-12 | Bahdanau Attention and Luong Attention | Bahdanau Paper | |
| Day120 | 2025-07-13 | Building a Seq2Seq Chatbot – Data Preparation & Preprocessing | PyTorch Tutorial | |
| Day121 | 2025-07-14 | Building a Seq2Seq Chatbot - Defining Model (encoder, attention, decoder) | Notebook | |
| Day122 | 2025-07-15 | Building a Seq2Seq Chatbot – Evaluation / Deployment | Live Demo | |
| Day123 | 2025-07-20 | Transformers – Deep Dive into Attention and Architecture | Attention Paper | |
| Day124 | 2025-07-21 | Transformers – Vitals (understanding everything) | Transformer Guide | |
| Day125 | 2025-07-22 | GPT from Scratch - Project Setup | Karpathy’s Tutorial | |
| Day126 | 2025-07-23 | GPT from Scratch - Bigram Language Model | Notebook | |
| Day127 | 2025-07-24 | GPT from Scratch - Self-Attention | Notebook | |
| Day128 | 2025-07-25 | GPT from Scratch – Complete Transformer | Notebook | |
| Day129 | 2025-07-26 | Image Captioning – Kickoff | Notebook | |
| Day130 | 2025-07-27 | Image Captioning – Feature Extraction & Pipeline | Notebook | |
| Day131 | 2025‑07‑28 | Image Captioning – Training & Deployment | Build a Large Language Model from Scratch | |
| Day132 | 2025‑07‑29 | Tokenizer Tricks (Subword, Byte-Pair Encoding) + Comparing Architectures | Build a Large Language Model from Scratch | |
| Day133 | 2025‑07‑30 | Implementing seq2seq (Diff Approach of Visualizations) | Build a Large Language Model from Scratch | |
| Day134 | 2025‑07‑31 | Implementing Transformer Encoder/Decoder Again | Build a Large Language Model from Scratch | |
| Day135 | 2025‑08‑01 | Pretraining on Unlabeled Data, Evaluating, Loading Pretrained Weights | Build a Large Language Model from Scratch | |
| Day136 | 2025‑08‑02 | Finetuning – Classification | Build a Large Language Model from Scratch | |
| Day137 | 2025‑08‑03 | Finetuning – Teaching LLMs to Follow Prompts and Perform Complex Tasks, Visualizations | Build a Large Language Model from Scratch | |
| Day137 | 2025‑08‑03 | Finetuning – Teaching LLMs to Follow Prompts and Perform Complex Tasks, Visualizations | Build a Large Language Model from Scratch | |
| Day138 | 2025‑08‑04 | LLM Fine-Tuning & Evaluation | Build a Large Language Model from Scratch | |
| Day139 | 2025‑08‑05 | Exploring Hugging Face Transformers | Build a Large Language Model from Scratch | |
| Day140 | 2025‑08‑06 | Project – Sentiment Analysis (Planning) + Exploring ViT | Notebook, Kaggle Code | |
| Day141 | 2025‑08‑07 | Project – Sentiment Analysis (Preprocessing) + ViT Architecture | Kaggle Code | |
| Day142 | 2025‑08‑08 | Project – Sentiment Analysis (EDA + Testing GloVe) | Notebook, Notebook, Kaggle Code | |
| Day143 | 2025‑08‑09 | Project – Sentiment Analysis (Advanced Architectures) | Notebook, Notebook, Kaggle Code | |
| Day144 | 2025‑08‑10 | Project – Sentiment Analysis (App Deployment) | Live Demo, Code | |
| Day145 | 2025‑08‑11 | Diving Deep into Vision Transformers (ViTs) | Blog | |
| Day146 | 2025‑08‑12 | Diving into Diffusion Models | Video | |
| Day147 | 2025‑08‑13 | Diffusion Model Deep Dive | Paper | |
| Day148 | 2025‑08‑15 | Naive Bayes & Gaussian Mixture Models | Langchain Playlist | |
| Day149 | 2025‑08‑17 | Introduction to Langchain | Langchain Playlist | |
| Day150 | 2025‑08‑18 | Introduction to Langchain Components | Langchain Playlist | |
| Day151 | 2025‑08‑19 | Deep Dive into Langchain Models | Langchain Playlist | |
| Day152 | 2025‑08‑20 | Langchain Prompts and Building a Simple Chatbot | Langchain Playlist | |
| Day153 | 2025‑08‑21 | Structured Output with Langchain | Langchain Playlist | |
| Day154 | 2025‑08‑23 | Langchain Output Parsers | Langchain Playlist | |
| Day155 | 2025‑08‑24 | Langchain Chain Fundamentals (Simple, Sequential, Parallel, Conditional Chains) | Langchain Playlist | |
| Day156 | 2025‑08‑25 | Langchain Runnables (Modular Components, Composable Workflows) | Langchain Playlist | |
| Day157 | 2025‑08‑26 | Runnable Modules Deep Dive (Sequence, Parallel, Passthrough, Lambda, Branch) | Langchain Playlist | |
| Day158 | 2025‑08‑27 | Document Loaders & Text Splitters (RAG Foundations) | Langchain Playlist | |
| Day159 | 2025‑08‑28 | Vector Stores in Langchain (Chroma, CRUD Operations, Similarity Search) | Langchain Playlist | |
| Day160 | 2025‑08‑29 | Retrievers & Few-Shot Learning (Wikipedia, Vector, MMR, MultiQuery, Contextual) | Langchain Playlist | |
| Day161 | 2025‑08‑30 | RAG Application for UCL Draw (Text Splitting, Vector Embeddings, Response Generation) | Langchain Playlist | |
| Day162 | 2025‑08‑31 | Langchain Tools (Built-in & Custom, Tool Calling & Binding) | Langchain Playlist | |
| Day163 | 2025‑09‑01 | Langchain Agents (Zero-Shot, Conversational, ReAct DocStore, Self-Ask) | Langchain Playlist | |
| Day164 | 2025‑09‑02 | Local Agent with Ollama & Langchain (ChromaDB, RAG) | Langchain Playlist | |
| Day165 | 2025‑09‑03 | Introduction to LangGraph (Stateful Agent Workflows) | Langgraph Playlist | |
| Day166 | 2025‑09‑04 | Agentic AI Fundamentals (Autonomy, Components, Planning, Memory) | Langchain Playlist | |
| Day167 | 2025‑09‑05 | LangChain vs LangGraph Comparison (State Management, Chatbot Example) | Langgraph Playlist | |
| Day168 | 2025-09-06 | Building a Branching Chatbot | Langgraph Playlist | |
| Day169 | 2025-09-07 | Persistence with Checkpoints | Langgraph Playlist | |
| Day170 | 2025-09-08 | Exploring LangSmith | Langgraph Playlist | |
| Day171 | 2025-09-11 | Contextual Q&A with Memory | Langchain Playlist | |
| Day172 | 2025-09-12 | Bhagavad Gita Expert Chatbot | Langgraph Playlist | |
| Day173 | 2025-09-13 | Multi-Agent Debating System | Langgraph Playlist | |
| Day174 | 2025-09-14 | Debate Agent App Completion | Langgraph Playlist | |
| Day175 | 2025-09-15 | Introduction to FastAPI for ML | FastAPI Documentation | |
| Day176 | 2025-09-16 | FastAPI Implementation | FastAPI Documentation | |
| Day177 | 2025-09-17 | HTTP Request Methods and REST Architecture | FastAPI Documentation | |
| Day178 | 2025-09-18 | FastAPI Parameters and Request Body | FastAPI Documentation | |
| Day179 | 2025-09-19 | Mini Project with FastAPI | FastAPI Documentation | |
| Day180 | 2025-09-20 | Building Industry-Ready APIs with FastAPI | FastAPI Documentation | |
| Day181 | 2025-09-23 | Containerizing FastAPI Applications | FastAPI Documentation | |
| Day182 | 2025-09-24 | fastapi deployment on aws | aws docs | |
| Day183 | 2025-09-25 | project setup – choose your own adventure | project repo | |
| Day184 | 2025-09-26 | database design and core components | project repo | |
| Day185 | 2025-09-27 | api implementation and background tasks | project repo | |
| Day186 | 2025-09-28 | backend completion and debugging | project repo | |
| Day187 | 2025-09-29 | frontend integration and project completion | project repo | |
| Day188 | 2025-10-01 | concurrency patterns in fastapi | starlette concurrency | |
| Day189 | 2025‑10‑02 | self-supervised learning – foundations | Lil’Log SSL Blog | |
| Day190 | 2025‑10‑03 | mcp and lazy week | Masked Conditional Prediction | |
| Day191 | 2025‑10‑04 | ssrl – image & video approaches | Lil’Log SSRL | |
| Day192 | 2025‑10‑05 | wrapping up ssl + fun reads | Postgres vs SQLite, GPT Speculations | |
| Day193 | 2025‑10‑06 | llama2 fine-tuning with qlora | QLoRA Fine-Tuning Guide | |
| Day194 | 2025‑10‑12 | gemma 2 fine-tuning using unsloth | Gemma2 Fine-tuning Notebook | |
| Day195 | 2025‑10‑13 | saving & loading lora adapters, explored “lora without regret” | LoRA Blog Post | |
| Day196 | 2025‑10‑14 | attempted RAG evaluation, faced compatibility issues | MCP Documentation | |
| Day197 | 2025‑10‑16 | built a custom MCP server, integrated with Cursor | Custom Implementation | |
| Day198 | 2025‑10‑18 | studied RL fundamentals: policies, MDPs, rewards | HuggingFace RL Course | |
| Day199 | 2025‑10‑20 | explored Q-learning & Deep Q-learning, lunar lander env | HuggingFace RL Course | |
| Day200 | 2025‑10‑21 | trained PPO agent on LunarLander-v3 using SB3 | HuggingFace RL Course |
View Full Details
For day-by-day logs, detailed notebooks, and code: GitHub Repository