Tag Archives: ML

Prediction of Tomorrow Rain in Australia

In this project, we aim to predict whether or not it will rain tomorrow by training a Random Forest classification model on target RainTomorrow. This dataset contains daily weather observations from numerous Australian weather stations. The data contains the following columns: Date: The date of observation Location: The common name of the location of the weather station MinTemp: The minimum temperature in degrees celsius MaxTemp: The maximum temperature in degrees celsius Rainfall: The amount of rainfall recorded …

Gender Recognition By Voice

Logistic Regression is a Machine Learning classification algorithm that is used to predict the probability of a categorical dependent variable. In logistic regression, the dependent variable is a binary variable that contains data coded as 1 (yes, success, etc.) or 0 (no, failure, etc.). We use Logistic Regression To predict whether an email is spam (1) or not (0), Whether the tumor is malignant (1) or not (0), To predict whether a voice/face man (1) …

Prediction of Pulsar Stars

The HTRU2 dataset describes a sample of pulsar candidates collected during the High Time Resolution Universe Survey. Pulsars are a rare type of Neutron star that produce radio emission detectable here on Earth. They are of considerable scientific interest as probes of space-time, the inter-stellar medium, and states of matter . As pulsars rotate, their emission beam sweeps across the sky, and when this crosses our line of sight, produces a detectable pattern of broadband …

Prediction of Shopping Behaviour

Stores are looking for new ways to promote their sale and increase their income. An increase can be found in cross-selling these days. Cross-selling is “an action or practice of selling an additional product or service to an existing customer”. It is important to understand how the products and services should be combined to increase their sale. It is the subject of a technique called Market Basket Analysis (MBA) or product association analysis.  Market Basket …

Prediction of Diabetes Occurrence​

In this project, we aim to predict the occurrence of diabetes within the PIMA Native American Group. We implemented the Decision Tree algorithm on Python. The data contains the following columns: times_pregnant: Number of times pregnant plasma_glucose: Concentration of plasma glucose in a 2 hour oral glucose tolerance test diastolic_blood_pressure: Measured in mmHg tricep_skin_fold_thickness: Measured in mm serum_insulin: Insulin concentration in serum in 2-hour period. Measured in (mu U/ml) body_mass_index: Weight in kg/height in (m^2) diabetes_pedigree_function: Function that assigns probability …

Prediction Of Iris Species

The Iris flower data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems. It is sometimes called Anderson’s Iris data set because Edgar Anderson collected the data to quantify the morphologic variation of Iris flowers of three related species. The data set consists of 50 samples from each of three species of Iris (Iris Setosa, Iris virginica, …

Prediction Of Startups Profit

In this project, we aim to predict the 50 startups profit. we implemented Multiple Linear Regression on Python. The data contains the following columns: R&D Spend Administration Marketing Spend State Profit . let’s get our environment ready with the libraries we’ll need and then import the data! Check out the Data . EDA Let’s create some simple plots to check out the data! . Training a Linear Regression Model Let’s now begin to train out …