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bintez

boston-housing-prices-multiple-regression

Going back to basics and trying to fit the famous Boston Housing Prices with our well known Multiple Regression.

collegare-connect

Range 2.0

concrete-strength-polynomial-regression

Here, we use Polynomial Regression in order to predict the concrete strength based on parameters like cement,ash,slag etc..,

decision-tree-regression-age-prediction-of-abalone

A decision tree is a flowchart-like structure in which each internal node represents a “test” on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes).

derma_care

do-you-have-diabetes-or-not-

Using the ML Dataset, we try to predict if a pima native American has diabetes or not. Here we use decision Tree Algorithm in order to make the predictions

dsa-problem-solving-series-by-testa-code

This repository contains the solutions for all the problems covered in the DSA Problem Solving Series by Testa Code. Also the assignment problems for each video is described here.

gradient-boosting-vehicle-prediction-silhouette-measurements-

We know that Foresting algorithms perform well in additive with some boosting techniques. Here we use Gradient Boosting in order to predict the type of vehicle based on silhouette measurements.

heart-disease-prediction-logistic-regression

Using the famous Logistic Regression to predict whether a person has Heart Disease or not.

iris-flower-type-prediction-logistic-regression-

Predicting the flower type of the Iris plant species using Logistic Regression

linear-regression-ols-vs-gradient-descent-

Starting from the basics!!! Yes Linear Regression is the first and simplest regression a ML enthusiast would have learnt. This repository is a very simple intuition on how OLS and Gradient Descent work for a simple Salary vs Experience Dataset

logistic-regression-fish-species-predictor

Logistic Regression, though by name is not a regression model. It performs classification. It must be known that this Algorithm is very important and has a separate importance though its an old one. Today everyone has moved towards Deep Learning, but it must be known that each neural unit performs the job of a Logistic Regression.

male-female-voice-detemination

Here, we try to determine male/female voice based on voice cahrac. The dataset is of a good number. So lets try to use Random Forest Algorithm to classify them

multiple-linear-regression-real-estate-price-prediction

Multiple linear regression (MLR), also known simply as multiple regression, is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.

polynomial-regression-boston-housing-prices

In order to improve the the predictions of the Boston Housing Dataset, we use the Poly Regression.

random-forest-age-of-the-abalone

The random forest is a supervised learning algorithm that randomly creates and merges multiple decision trees into one “forest.” The goal is not to rely on a single learning model, but rather a collection of decision models to improve accuracy. The primary difference between this approach and the standard decision tree algorithms is that the root nodes feature splitting nodes are generated randomly.

shopping-mall-customer-analysis-k-means-clustering

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data mining, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Here we try to analyse the customers visiting the Shopping Mall

stopapsci

An AI based Stone-Paper-Scissors Game with Simpson

support-vector-machine-classification---liver-disease-prediction

We use a specialized algorithm , the SVMs in order to predict if a person is suffering from a liver disease based on the given attributes.

svm-classification-balance-scale-

SVMs, one of the most complicated ML algorithms. We try to predict on which way the tip of a balance scale moves using SVM Classification.

wine-data-classification-adaboost

Here, we use the famous wine dataset to classify the type of wine. In this approach, we can use many algorithms. But am using AdaBoost in order to see how the week learners combine together to form a strong learner