Getting started with Predictive Analysis
by Sri Balaji J Updated: Jun 13, 2022
Scikit-learn (Sklearn) is the most useful and robust library for machine learning in Python. It provides a selection of efficient tools for machine learning and statistical modeling including classification, regression, clustering, and dimensionality reduction via a consistence interface in Python.
In Classification, the output variable must be a discrete value. The task of the classification algorithm is to map the input value(x) with the discrete output variable(y).
Convolutional Neural Network for Text Classification in Tensorflow
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Chinese text classification, TextCNN, TextRNN, FastText, TextRCNN, BiLSTM_Attention, DPCNN, Transformer, based on pytorch, out of the box.
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Classification with PyTorch.
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In Regression, the output variable must be of continuous nature or real value. The task of the regression algorithm is to map the input value (x) with the continuous output variable(y).
Module for adding visual regression testing to Cypress
Backend and Frontend application for tracking differences via image comparison
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A way of grouping the data points into different clusters, consisting of similar data points. The objects with the possible similarities remain in a group that has less or no similarities with another group.
MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
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This project allows images to be automatically grouped into like clusters using a combination of machine learning techniques.
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Email clustering with machine learning
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It is a way of converting the higher dimensions dataset into lesser dimensions dataset ensuring that it provides similar information.
Feature selector is a tool for dimensionality reduction of machine learning datasets
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Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
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Using siamese network to do dimensionality reduction and similar image retrieval
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Model selection is the process of selecting one final machine learning model from among a collection of candidate machine learning models for a training dataset.
Visual analysis and diagnostic tools to facilitate machine learning model selection.
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Auto Tune Models - A multi-tenant, multi-data system for automated machine learning (model selection and tuning).
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Easily render backbone.js collections. In addition to managing model views, this class supports automatic selection of models in response to clicks, reordering models via drag and drop, and more.
Data preprocessing is a process of preparing the raw data and making it suitable for a machine learning model. It is the first and crucial step while creating a machine learning model.
Utilities for working with image data, text data, and sequence data.
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Python Whole Slide Image Preprocessing
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😎 Finding duplicate images made easy!
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