Python Scripts and Jupyter Notebooks

Kaggle Kernels (Python, R, Jupyter Notebooks)

JupyterLab Notebook for Mesosphere DC/OS

Analytics labs notebooks for Statistics and Business School students

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

预测rossmann1115家商店未来的销售额

Allstate Kaggle Competition ML Capstone Project

Data Science Feature Engineering and Selection Tutorials

A container for Deep Learning with Python 3

Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques.

My contributions in Kaggle, mostly in a notebook format. Just for fun.

Machine Learning Operator & Controller for Kubernetes

A jupyter notebook for binary classification of breast cancer using XGBoost with Bayesian optimization.

📓 📈 Functions from Abhishek Thakur's book Approaching (Almost) Any Machine Learning Problem.

Bunch of notebooks collection from Kaggle competitions.

Container-ready Jupyter Notebook application based on a TensorFlow 2.12.0/Python 3.10 image, utilizing XGBoost model training for structured data

Data & Scripts for the Memorial Sloan Kettering Cancer Center's (MSKCC) request for a machine learning algorithm that, using annotated information on genomic variants, automatically classifies genetic variations as either neutral or cancerous.

In this notebook, we will create an AI and time serie driven forecasting engine based on a set of 5 AI models and 5 time series models and employ several algorithms to perform feature engineering and selection on a multivariate time series dataset.

In this Amazon SageMaker tutorial, you'll find labs for setting up a notebook instance, feature engineering with XGBoost, regression modeling, hyperparameter tuning, bring your custom model etc.

This notebook is ispired by the AIX360 HELOC Credit Approval Tutorial, which shows different explainability methods for a credit approval process. Here XGBoost is used for classification, achieving better accuracy than most of the models used in that notebook. Then, feature importance methods are shown, to be compared with the Data Scientist exp…