Team-fastML / fastMLLinks
A Python package built on sklearn for running a series of classification Algorithms in a faster and easier way.
☆54Updated last year
Alternatives and similar repositories for fastML
Users that are interested in fastML are comparing it to the libraries listed below
Sorting:
- A python package built for data scientist/analysts, AI/ML engineers for exploring features of a dataset in minimal number of lines of cod…☆21Updated 4 years ago
- Powerful rapid automatic EDA and feature engineering library with a very easy to use API 🌟☆53Updated 3 years ago
- Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib☆19Updated 3 years ago
- State-of-the-art question answering with HuggingFace and Streamlit☆19Updated 4 years ago
- Best practices for engineering ML pipelines.☆35Updated 3 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
- ☆17Updated 4 years ago
- Creating a Gradio user interface to predict the sentiment of a tweet☆11Updated 3 years ago
- Build tensorflow keras model pipelines in a single line of code. Now with mlflow tracking. Created by Ram Seshadri. Collaborators welcome…☆121Updated last year
- Tensorflow object detection api in single line☆12Updated 3 years ago
- ☆26Updated 4 years ago
- A comprehensive tool for linguistic analysis of communities☆49Updated 3 years ago
- Deep Learning Projects on TensorFlow and Keras☆20Updated last year
- Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.☆65Updated 4 months ago
- A Recommendation engine for an e-commerce use case that provides recommendations to users based on their purchase history.☆21Updated 3 years ago
- ☆16Updated 4 years ago
- TensorFlow Serving + Streamlit!☆22Updated 3 years ago
- This repository contain the projects related with -- time series data☆11Updated 4 years ago
- Content for Applied ML Workshop @ DataHack Summit 2019