Machine Learning - The Algorithms

The Algorithms

Machine Learning

Xgboost Regressor

Xgboost Classifier

Data Transformations

Decision Tree

Scoring Functions

Run

Self Organizing Map

Word Frequency Functions

Local Weighted Learning

Dimensionality Reduction

Polymonial Regression

Logistic Regression

Support Vector Machines

Linear Discriminant Analysis

Similarity Search

Astar

Gradient Descent

K Nearest Neighbours

Multilayer Perceptron Classifier

Knn Sklearn

Lstm Prediction

K Means Clust

Linear Regression

Sequential Minimum Optimization

Neural Network

Ordinary Least Squares Regressor

Kohonen Som Trace

Adaline Learning

A Star Search

Kohonen Som Topology

K Nearest Neighbors

Vector Ops

K Means Clustering

Piecewise Linear Transform

Matplotlib

ARIMA with Pyramid

Random Forest Classifier

Basic of Tensor Flow

Naive Bayes

Fundamentals of Numpy

Image Denoising Using Numpy

Face Recognition Using Eigen Faces

Random Forest Regression

Movie Recommendation System

Python Basics

Scikit-Learn

Support Vector Machine

Named Entity Recognition with Conditional Random Fields

Movie Recommendation Sentance Embedding

Reuters One vs Rest Classifier

Association

Prophet

Pandas

Naive Bayes Classification

K-Fold Cross-Validation of Decision Tree Regression

House Price Prediction

Dbscan

Price Prediction Model

Linear Regression Using Pandas

Similarity

Brightness

Computecost

Run Linear Regression

Plotdata

Run Logistic Regression

Costfunction

Plotdecisionboundary

Predict

Piecewise(without Inbuilt)

Parametric Re LU

Threshold(without Inbuilt)

Hyperbolic tangent(without Inbuilt)

Leaky Re LU

ELU

Linear(without Inbuilt)

GELU

Re LU 6

Sigmoid(without Inbuilt)

ML

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