Machine Learning - The Algorithms

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Machine Learning

K Means Clust

Polynomial Regression

Linear Discriminant Analysis

Run

Scoring Functions

Support Vector Machines

Gradient Descent

Decision Tree

Xgboost Classifier

Local Weighted Learning

Dimensionality Reduction

Data Transformations

Similarity Search

Linear Regression

Knn Sklearn

Lstm Prediction

Sequential Minimum Optimization

Multilayer Perceptron Classifier

Logistic Regression

Word Frequency Functions

K Nearest Neighbours

Self Organizing Map

Xgboost Regressor

Vector Ops

Kohonen Som Topology

Ordinary Least Squares Regressor

K Nearest Neighbors

Neural Network

A Star Search

Kohonen Som Trace

Adaline Learning

K Means Clustering

Random Forest Classifier

ARIMA with Pyramid

K-Fold Cross-Validation of Decision Tree Regression

Similarity

Basic of Tensor Flow

Scikit-Learn

Python Basics

Prophet

Association

Dbscan

Fundamentals of Numpy

Face Recognition Using Eigen Faces

Image Denoising Using Numpy

Price Prediction Model

Support Vector Machine

Pandas

Named Entity Recognition with Conditional Random Fields

Movie Recommendation Sentance Embedding

Random Forest Regression

Matplotlib

Movie Recommendation System

Reuters One vs Rest Classifier

Linear Regression Using Pandas

Naive Bayes Classification

Piecewise Linear Transform

House Price Prediction

Naive Bayes

Plotdata

Run Linear Regression

Computecost

Sigmoid(without Inbuilt)

Leaky Re LU

Piecewise(without Inbuilt)

GELU

ELU

Re LU 6

Threshold(without Inbuilt)

Hyperbolic tangent(without Inbuilt)

Linear(without Inbuilt)

Parametric Re LU

Run Logistic Regression

Plotdecisionboundary

Predict

Costfunction

Brightness

ML

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