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A curated list of awesome Python asyncio frameworks, libraries, software and resources
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud.
Run PyTorch LLMs locally on servers, desktop and mobile
The fastest way to create an HTML app
A game theoretic approach to explain the output of any machine learning model.
Exploring some issues related to churn
This project integrates the Python, SQL and Tableau and demonstrates the working of end-to-end data science project
A Python script to generate buy/sell signals using Simple moving average(SMA) and Exponential moving average(EMA) Crossover Strategy.
A 4-hour coding workshop to understand how LLMs are implemented and used
DSPy: The framework for programming—not prompting—foundation models
Jupyter Notebooks demonstrating Optimization using Python with case studies
Discrete Event simulation of a queue using Python.
Get up and running with Llama 3.1, Mistral, Gemma 2, and other large language models.
This repository contains free labs for setting up an entire workflow and DevOps environment from a real-world perspective in Azure
Python code for common Machine Learning Algorithms
Survival analysis built on top of scikit-learn
Improving XGBoost survival analysis with embeddings and debiased estimators
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Hands-On Survival Analysis in Python
🛠️ T-SQL scripts for the long haul: optimizing storage, on-the-fly documentation, and general administrative needs.
Customer Churn Prediction with data from Kaggle
In this repository, customer churn prediction was carried out with the help of CatBoost Classifier and an accuracy of 81.54% was obtained.The Customer Churning dataset was obtained from kaggle.
Customer churn prediction modeling using XGBoost, LightGBM, CatBoost, and SVM
Python - Tuning parameters of XGBoost alogrithm using Cross-Validation
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research