AutoViML / deep_autoviml
Build tensorflow keras model pipelines in a single line of code. Now with mlflow tracking. Created by Ram Seshadri. Collaborators welcome. Permission granted upon request.
☆120Updated 6 months ago
Related projects ⓘ
Alternatives and complementary repositories for deep_autoviml
- Build Low Code Automated Tensorflow explainable models in just 3 lines of code. Library created by: Hasan Rafiq - https://www.linkedin.co…☆181Updated last year
- Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.☆64Updated 9 months ago
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆88Updated 10 months ago
- This repository is to host template for calculating ROI on Artificial Intelligence projects☆44Updated 5 years ago
- Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking☆55Updated 3 years ago
- 100 applications built with H2O Wave☆99Updated 2 years ago
- Example machine learning pipeline with MLflow and Hydra☆87Updated last year
- NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for …☆106Updated 2 years ago
- PyCaret and Streamlit app deployment on Heroku☆69Updated 3 years ago
- Feature engineering package with sklearn like functionality☆50Updated 2 months ago
- Pre-processing database using pre-written functions☆20Updated 4 years ago
- Simple & Easy-to-use python modules to perform Quick Exploratory Data Analysis for any structured dataset!☆100Updated last year
- Powerful rapid automatic EDA and feature engineering library with a very easy to use API 🌟☆53Updated 2 years ago
- A hands-on case study for demonstrating the stages involved in a machine learning project, from EDA to production.☆37Updated last year
- An end-to-end project on customer segmentation☆82Updated last year
- Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage deep learning and deep tr…☆49Updated last year
- Data Analysis Baseline Library☆131Updated 3 weeks ago
- Introduction to MLflow with a demo locally and how to set it on AWS☆42Updated 3 years ago
- ☆26Updated 3 years ago
- Streamline scikit-learn model comparison.☆146Updated last year
- Slides for "Feature engineering for time series forecasting" talk☆57Updated 2 years ago
- Categorical Embedder is a python package that let's you convert your categorical variables into numeric via Neural Networks☆25Updated 4 years ago
- 🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.☆143Updated 7 months ago
- Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upo…☆524Updated 4 months ago
- Content for Applied ML Workshop @ DataHack Summit 2019☆25Updated 5 years ago
- Machine Learning begins with Human Learning☆108Updated 3 years ago
- ☆17Updated 2 years ago
- This workshop was done as a part of the 1729 conference organized by Fractal Analytics and Analytics Vidhya. Key content covered was hand…☆21Updated 2 years ago
- Microservice creation and Machine Learning Model Deployment using FastAPI☆113Updated 2 years ago
- Jupyter Notebooks and other material from tutorial sessions on Machine Learning, Data Science, and related☆56Updated 3 years ago