The repository was created to track my progress in Machine Learning related topics in order to organize my knowledge and goals. Includes machine learning projects and showcases in Scikit-Learn, TensorFlow, and Keras.
Problem | Description | Tech Stack | Dataset | Creation Date | Last Update |
---|---|---|---|---|---|
The Simpsons Characters Classification | CNN, 4 and 6 convolutions, dropout-regularization, data-augmentation | TensorFlow, Matplotlib, Flask, Numpy | Kaggle | 9/15/2019 | 10/27/2019 |
Titanic Disaster Survivor Prediction | XGBoost | XGBoost, Numpy, Pandas, Matplotlib, Seaborn, GridSearch | Kaggle | 08/9/2022 | 08/27/2022 |
House Prices Prediction with SKLearn Pipeline | 10 Regression Models, Hyperparameter search using GridSearch and RandomizedSearchCV, SKLearn Pipeline | SKLearn, LightGBM, CatBoost, XGBoost, Numpy, Pandas, Matplotlib, Seaborn, GridSearch, RandomizedSearchCV | Kaggle | 12/15/2022 | 12/26/2022 |
ML Pipeline for Short-Term Rental Prices in NYC | End to end ML pipeline to predict rental prices for airbnb rentals using MLFlow and Weights and Biases | MLOps, SKLearn, Numpy, Pandas, Matplotlib, GridSearch, MLFlow, Weights and Biases, Pytest | Kaggle | 1/5/2022 | 1/11/2022 |
Salary Predictor Application with FastAPI | Salary prediction model deployed with FastAPI, DVC pointing to AWS S3 bucket, unit tests and API tests, CI/CD framework using GitHub Actions | MLOps, SKLearn, Numpy, Pandas, Matplotlib, FastAPI, Pytest, AWS, CI/CD | Census Bureau | 1/15/2022 | 1/21/2022 |
In this section I want to present my knowledge about various ML related algorithms, frameworks, programming languages, libraries and more. Priority is to show how the algorithm works - not to solve complex and ambitious problems.
Algorithm | Problem | Description | Dataset | Creation Date | Last Update |
---|---|---|---|---|---|
Linear Regression | Childhood Respiratory Disease | Raw Python | Dataset | 07/20/2022 | 08/27/2022 |
Logistic Regression | Gender Recognition by Voice and Speech Analysis | Raw Python | Dataset | 07/25/2022 | 08/27/2022 |
Gaussian Distribution Anomaly Detection | Anomaly Detection | Raw Python | Dummy Data | 08/29/2022 | 10/15/2022 |
Decision Tree | Mashroom Classification | Raw Python | Dummy Data | 08/10/2022 | 10/15/2022 |
K-means | K-means Clustering | Raw Python | Dummy Data | 08/15/2022 | 10/15/2022 |
Algorithm | Problem | Description | Dataset | Creation Date | Last Update |
---|---|---|---|---|---|
MLP | Coffee Roast | 2 layers, Raw Python | Dummy Data | 09/07/2022 | 10/15/2022 |
Algorithm | Problem | Description | Dataset | Creation Date | Last Update |
---|---|---|---|---|---|
Linear Regression | Childhood Respiratory Disease | Sklearn | Dataset | 08/19/2019 | 10/20/2019 |
Logistic Regression | Gender Recognition by Voice and Speech Analysis | Sklearn | Dataset | 08/25/2019 | 10/19/2019 |
KNN | Diabetes Test | Sklearn | Dataset | 08/30/2019 | 10/20/2019 |
SVM | Exoplanets | Sklearn | Dataset | 9/18/2019 | 10/20/2019 |
Random Forest | Diabetes Test | Sklearn | Dataset | 9/24/2019 | 10/20/2019 |
K-means | K-means Clustering | Sklearn | Dummy Data | 9/26/2019 | 10/20/2019 |
Net Type | Problem | Description | Dataset | Creation Date | Last Update |
---|---|---|---|---|---|
CNN | Cats vs Dogs | 3 convolutions | Microsoft | 10/07/2019 | 10/27/2019 |
CNN | Horses vs Humans | InceptionV3, dropout-regularization, data-augmentation | Dataset | 10/14/2019 | 10/27/2019 |
CNN | Sign Language Detector | 2 convolutions, data-augmentation | Sign Language MNIST | 10/19/2019 | 10/29/2019 |
Net Type | Problem | Description | Dataset | Creation Date | Last Update |
---|---|---|---|---|---|
MLP | BBC News Classification | 3 layers, global average pooling | BBC Archive | 10/23/2019 | 11/05/2019 |
RNN | Poem Generator | Bidirectional LSTM, dropout | Shakespeare Sonnets | 10/23/2019 | 10/05/2019 |
CNN/RNN | Twitter Sentiment Analysis | Max pooling, LSTM, dropout-regularization, NTLK | Kaggle | 11/13/2019 | 12/10/2019 |
Net Type | Problem | Description | Dataset | Creation Date | Last Update |
---|---|---|---|---|---|
CNN/RNN | Sunspot Prediction | 1 convolution, 2 LSTM | Github | 10/29/2019 | 11/17/2019 |
Net Type | Problem | Description | Dataset | Creation Date | Last Update |
---|---|---|---|---|---|
MLP | Smartphone Activity Detector | 3 layers with 1 hidden layer, ReLu, Softmax, Adam Optimizer | Dataset | 10/03/2019 | 10/20/2019 |
MLP | Credit Card Fraud Detection | 4-layers, dropout-regularization | Kaggle | 11/07/2019 | 11/24/2019 |
Linear Regression | Gold Futures Prediction | TensorFlow | Investing.com | 11/17/2019 | 11/29/2022 |
Linear Regression | Collaborative Filtering Recommender System | TensorFlow, Recommender System | MovieLens | 9/27/2022 | 10/17/2022 |
MLP | Content-Based Filtering Recommender System | TensorFlow, Recommender System | MovieLens | 9/30/2022 | 10/17/2022 |
Reinforcement Learning | Lunar Lander | TensorFlow | OpenAI Gym | 9/30/2022 | 10/17/2022 |
- Mathematics for Machine Learning Specialization (Coursera - Imperial College London)
- Intro to Statistics (Udacity)
- Intro to Inferential Statistics (Udacity)
- Data Structures and Algorithms Course in Python (Udemy)
- Machine Learning Specialization (Coursera - Stanford - Andrew Ng)
- DeepLearning.AI TensorFlow Developer Specialization (Coursera - deeplearning.ai)
- Introduction to Machine Learning in Production (Coursera - deeplearning.ai)
- Deep Learning Specialization (Coursera - deeplearning.ai)
- Machine Learning DevOps Engineer (Udacity Nanodegree)
Notes from some of the courses above - Notes