🔭 Currently working on: Recommender Systems with PySpark.
- ✔️ Content-Based Recommender Systems: Jaccard and Cosine Similarities, TF-IDF, Word2Vec + LSH and SVD.
- ✔️ User-Based Recommender Systems: Cosine Similarity and ALS (Alternating Least Squares).
- 🔲 Cold Start Problem.
- 🔲 Streaming Updates: update models in real time.
- 🔲 Handling cache for real time responses (Spark Structured Streaming or Kafka, not sure yet).
🔭 Also working on: Building Machine Learning Models From Scratch.
- ✔️ Simple Linear Regression Model.
- ✔️ Multivariate Regression Model.
- ✔️ Logistic Regression: multivariate, but only 2 classes in target variable.
- ✔️ Multinomial Logistic Regression: multivariate and multiple classes in target variable.
- ✔️ Regularization Techniques: Ridge, Lasso and Elastic-Net.
- ✔️ Gradient Descent Optimization: batch size modifications, momentum and adaptive methods.
- 🔲 Support Vector Machine (SVM).
- 🔲 Neural Network.
📝 Side Projects:
- Simulations with Python (SimPy) and R (simmer), and visualization (animated plots and PyGame).
- AI bot to summarize Data Science news.
- Image-to-Text business notes taken by hand for further processing.