devdatta95/Numpy_Exercise

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devdatta95/Numpy_Exercise

devdatta95

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NumPy is a computational library that helps in speeding up Vector Algebra operations that involve Vectors (Distance between points, Cosine Similarity) and Matrices. Specifically, it helps in constructing powerful n-dimensional arrays that works smoothly with distributed and GPU systems. It is a very handy library and extensively used in the domains of Data Analytics and Machine Learning. Other than Python, it can also be used in tandem with languages like C and Fortran. Being an Open Source Library under a liberal BSD license, it is developed and maintained publicly on GitHub.

Python_Exercise

These Python programming exercises are suitable for all Python developers. If you are a beginner, you will have a better understanding of Python after solving these exercises.

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Pandas_Exercise

The purpose of this repository to show various Excel tasks that can be executed using Pandas library in python

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OCR_Documents_With_Flask

This flask web applications extract the text data from documets photos like adhar card, pan card, driving licesnce, Bank Cheque and Others, It also detected the face present in the document and store it in the face folder

Python-Practice

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Basics-of-Python-Programming-For-Data-Science

This repository contains all the fundamentals of Python programming. which is mostly used in Data science and machine learning algorithm

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Fashion-Class-Classification-Using-CNN

The global fashion industry is valued at three trillion dollars and accounts for 2 percent of the world's. GDP the fashion industry is undergoing a dramatic transformation by adopting new computer vision and Machine learning and deep learning techniques. In this case study we'll look at a hypothetical situation. We assume that if a retailer hired you to build a virtual stylist assistant that looks at customer Instagram and Facebook images and classifies what fashion category they are wearing either bags dresses and pants. The virtual assistant can help the retailer detect and forecast fashion trends and launch targeted marketing campaigns. In this story we're going to use the fashionmnist data. It's a data set that contains images of bags shoes and dresses. And we're asking the deep network to classify the images into 10 classes. So we wanted to build kind of an app per se or a model. They can look at images and can tell us exactly what category in this image. Is it like a short. Is it a bag. Is it like a hat. And so on. That's the whole objective. The data again they are divided into 28 by 28 greyscale images and the target class is actually No. 1 out of 10 which is kind of a target label which can be categorized as you can see into either like maybe a shoe maybe like like pants. Basically these are the target classes. We have the t shirts trousers pullovers ankle boots sneakers and so on so forth.

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SQL_Poject

folder to save sql codes

PGA13-Face-Dection

this project is used to train LBPH model for face recognition and haarcasde for detection

Linear-Regression-In-Python

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XYZ-Corporation-Lending-Data-Project

People often save their money in the banks which offer security but with lower interest rates. Lending Club operates an online lending platform that enables borrowers to obtain a loan, and investors to purchase notes backed by payments made on loans. It is transforming the banking system to make credit more affordable and investing more rewarding. But this comes with a high risk of borrowers defaulting the loans. Hence there is a need to classify each borrower as defaulter or not using the data collected when the loan has been given.

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Credit-Card-Fraud-Detection

In this project I use various Machine Learning models and Deep learning models such as ANN to see how accurate they are in detecting whether a transaction is a normal payment or a fraud.

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Simple-Linear-Regression

Simple linear regression is supervised machine learning algorithm. which is use to find the relationship between one independent variable and one dependent variable. The data-set contain 2 variable one is dependent which is Salary and the other is Experience. so with the help of these data we have to predict the salary based on the Years of Experience.

adbc

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Project-VGG16

this project is used classification

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SVM-PROJECT

this project is used to predict loan status

Polynomial-Regression-For-Salary-Prediction

A simple R program that implements a very basic Polynomial Regression on a small data set. Because these data set don't have liner relationship between independent variable and dependent variable. so if we use the liner model then well get very High error. so in these example w'll compare both the model and select which one is best.

linear-regression

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PGA23-ML-TEST

this project is used for model builidng

Market-Basket-Analysis-On-Retail-store-in-R

Market Basket Analysis is one of the key techniques used by large retailers to uncover associations between items. It works by looking for combinations of items that occur together frequently in transactions. To put it another way, it allows retailers to identify relationships between the items that people buy.

FACE-PGA17

this project is tokk apsdfjlaskdfjl asdlfkja sldkfjlaskdfj asdlkfjasldkfja;sdlkfja;sldkfj asd;lfkjasd f;l

Classification-on-Indian-liver-Patient

The given data set is related to Indian patients who have been tested for a liver disease. Based on chemical compounds (bilrubin,albumin,protiens,alkaline phosphatase) present in human body and tests like SGOT, SGPT the outcome mentioned is whether person is a patient i.e, whether he needs to be diagnosed further or not. Perform data cleansing, and required transformations and build a predictive model which will be able to predict most of the cases accurately. Following are the feature names for the given data: Age,Gender,Total_Bilirubin,Direct_Bilirubin,Alkaline_Phosphotase, Alamine_Aminotransferase,Aspartate_Aminotransferase,Total_Protiens,Albumin, Albumin_and_Globulin_Ratio,Class.

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faq2

test-4

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