ibah
Data scientist experienced in creating machine learning solutions and leading project and teams for large companies.
Mercer Services PolandWarsaw, Poland
Pinned Repositories
aie4
ajcr.github.io
Write-ups of things I've puzzled over
analysis-HousingPrices
Predicting housing prices (Seattle, US)
coursera-Regression_Models-project
Regression Models course by JHU at coursera. Project.
guide
A guide into other repositories and resources.
Introduction-to-Statistical-Learning
R code covering the Introduction to Statistical Learning book - reproducing examples, figures, solving exercises.
kaggle-leaf-classification
Models for the Leaf Classification competition at Kaggle.
kaggle-Lending_Club_dataset
Exploration and predictive models for Lending Club dataset at Kaggle
python-study
Learning & experimenting with python: pandas, computational statistics.
scikit-learn
scikit-learn: machine learning in Python
ibah's Repositories
ibah/Introduction-to-Statistical-Learning
R code covering the Introduction to Statistical Learning book - reproducing examples, figures, solving exercises.
ibah/kaggle-Lending_Club_dataset
Exploration and predictive models for Lending Club dataset at Kaggle
ibah/scikit-learn
scikit-learn: machine learning in Python
ibah/aie4
ibah/analysis-HousingPrices
Predicting housing prices (Seattle, US)
ibah/book-BrianCaffo
Analyses and solution to exercises for data science books by Brian Caffo / JHU
ibah/coursera-Regression_Models-project
Regression Models course by JHU at coursera. Project.
ibah/guide
A guide into other repositories and resources.
ibah/kaggle-leaf-classification
Models for the Leaf Classification competition at Kaggle.
ibah/python-study
Learning & experimenting with python: pandas, computational statistics.
ibah/coursera-Reproducible_Research-project_2
Reproducible Research course by JHU at coursera. Project 2.
ibah/coursera-Statistical_Inference-project
Statistical Inference course by JHU at coursera. Project.
ibah/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
ibah/Fine-Tuning-LLMs-for-Medical-Entity-Extraction
Exploring the potential of fine-tuning Large Language Models (LLMs) like Llama2 and StableLM for medical entity extraction. This project focuses on adapting these models using PEFT, Adapter V2, and LoRA techniques to efficiently and accurately extract drug names and adverse side-effects from pharmaceutical texts
ibah/first-llm-app
ibah/Forecasting_with_R_practices
Forecast using R language. The problems are from 'Forecasting: Principles and Practice(2nd ed.)'.
ibah/ipipan-Advanced_Statistical_Methods-solutions
Solutions to problem sets from Advanced Statistical Methods e-learning course by IPI PAN - cover modules 1-4.
ibah/kaggle-outbrain-click-prediction
ibah/kaggle-Titanic--Python-
Python (scikit-learn) model for Kaggle competition on Titanic passenger survival (classification).
ibah/kaggle-Titanic--R-
Data exploration and a simple model for Titanic competition at Kaggle.
ibah/llm-app
ibah/numpy-100
100 numpy exercises (100% complete)
ibah/Projects
My personal projects. Check them out!
ibah/public-aie3-solutions
ibah/python-extracts
Extracts of python code to serve as a reference.
ibah/R-extracts-visualizations
Extracts of R code for visualizations to serve as a reference.
ibah/seer-nest
Nest full of little prophets about to hatch.
ibah/sta-663-2017
Notebooks, worksheets and homework for STA 663 class
ibah/tf_app
TensorFlow - getting started
ibah/ThinkStats2
Text and supporting code for Think Stats, 2nd Edition