SRINIVASARAO K S's repositories
ARIMA-Time-Series-Model
ARIMA is an acronym that stands for AutoRegressive Integrated Moving Average. It is a class of model that captures a suite of different standard temporal structures in time series data. In statistics and econometrics, and in particular, in time series analysis, an autoregressive integrated moving average model is a generalization of an autoregressive moving average model. Both of these models are fitted to time series data either to better understand the data or to predict future points in the series.
Clustering
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups.k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. In this Repository tried to explain about K-Means and how the elbow method will help to decide K values
DecisionTree
Data were extracted from images that were taken from genuine and forged banknote-like specimens. For digitization, an industrial camera usually used for print inspection was used. The final images have 400x 400 pixels. Due to the object lens and distance to the investigated object gray-scale pictures with a resolution of about 660 dpi were gained. Wavelet Transform tool was used to extract features from images.
KNN_algorithm
The datasets consists of several medical predictor variables and one target variable, Outcome. Predictor variables includes the number of pregnancies the patient has had, their BMI, insulin level, age, and so on.
LinearRegression
linear regression is a linear approach to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). The case of one explanatory variable is called a simple linear regression. One of the most known and used algorithms that most of tech_specialist use and love is Linear Regression. Tried to solve it with a dataset
PCA
The principal components of a collection of points in a real p-space are a sequence of direction vectors, where the vector is the direction of a line that best fits the data while being orthogonal to the first vectors.As in PCA (Principal Component Analysis) Sharing you about how correlation and covariance helps to decide and usage of PCA
Logistic_Regression
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.).
SalesDashboard
Sales across USA using Tableau
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)