General Assembly's 2015 Data Science course in Washington, DC
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Updated
Oct 6, 2022 - Jupyter Notebook
General Assembly's 2015 Data Science course in Washington, DC
Machine Learning notebooks for refreshing concepts.
Local Interpretable Model-Agnostic Explanations (R port of original Python package)
An Interactive Approach to Understanding Deep Learning with Keras
Use AutoAI to detect fraud
🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.
CloudCV GSoC Ideas
This project analyzes and visualizes the Used Car Prices from the Automobile dataset in order to predict the most probable car price
an MLOps/LLMOps platform
A High-level Scorecard Modeling API | 评分卡建模尽在于此
Solve complex real-life problems with the simplicity of Keras
Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn.
An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering, hyperparameter optimization, model evaluation, and cross-validation with a variety of ML techniques and MLP
Analyzing the Features which leads to heart diseases and visualizing the models' performance and important features using eli5, shap and pdp.
Flexible tool for bias detection, visualization, and mitigation
UBC ARBERT and MARBERT Deep Bidirectional Transformers for Arabic
Python tools for the AeroCom project
Measure and visualize machine learning model performance without the usual boilerplate.
Rapid Calculation of Model Metrics
🎓 2020 Undergraduate Graduation Project in Jiangnan University ALL codes including Data-convert, keras-Train, model-Evaluate and Web-App
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