Sarthak Niwate's repositories
Hackerrank-Python-3-Solutions
Hackerrank being the top platform to test your coding skills and optimize the way of writing code as you practice more. I have shared the solutions of questions which I solved and the test cases were passed and solution is accepted.
CNN-Fashion-MNIST-Data-Analysis
Fashion MNIST dataset is famous dataset of 60000 raw images of fashion clothes. We have to categories and identify the type of clothes.
Data-Stucture-and-Algorithms-Programs
Add DS Programs in any language.
Exploratory-Data-Anlysis-Basics-with-Referee-Dataset
Creating a small subgroup of data set values from a huge data. The tables created in the file are players and clubs. You can try out more because the helping function is already created in the file.
Hackerrank-Data-Structures-Solutions
Every problem from hackerrank Data Structures will be uploaded with solution and problem url.
Hackerrank-SQL-Solutions
Every problem from hackerrank SQL will be uploaded with solution and problem url.
Java-Programs
Share your Java Programs here.
Mathematizer
Add your codes related to mathematics.
Python-Master-Coding
I have clubbed the programming problems, concepts, small basic algorithms like the bubble sort, etc., complexity problems related to order(N).
Python-Programs
Add any python programs here
Temperature-Humidity-Regression-Analysis
This simple small project is all about analyzing 72 readings of temperature and humidity. Using Linear Regression, the analysis of past readings and forecast is shown in the two different graphs of temperature and humidity. The project is simply coded and anyone who knows the basics can easily understand the logic and implementation. The most valuable features like reshape, fit_transform, polynomial feature with degree n, applying model, predicting and forecasting with the graphical representation in the end.
Boston-Data-Analysis-using-TensorFlow-Keras
the Housing dataset which contains information about different houses in Boston. This data was originally a part of UCI Machine Learning Repository and has been removed now. We can also access this data from the scikit-learn library. There are 506 samples and 13 feature variables in this dataset. The objective is to predict the value of prices of the house using the given features.
Regression-Project-Bangalore-House-Price-Prediction
The Bangalore House Price Dataset is taken from kaggle source. The data set is all about flat housing property and its features. The most tedious task in this dataset was data cleaning. It took lot of time and good logics to be resolved and get the optimized dataset. Else the another tasks of One Hot Encoding, Model Building are more of self-explanatory, if your basics are good and you know something about it before reading this project. In the end using GridSearchCV, I have tested the accuracy of model with comparing with one another model and then predicted the prices of properties/houses on the basis of some features. I hope you will enjoy it! Happy Learning!
Machine-Learning-Concepts
The essential algorithms of Supervised Learning and Unsupervised Learning will be explained in this repository. I have taken the guidance of YouTube Channel "Code Basics" for the data sets and references.
SarthakNiwate_week_1
These are tasks completed during Python Data Engineer Internship at Chistats Labs. Guided by Girish Bamane, Umaima Surti.
SarthakNiwate_week_2
These are tasks completed during Python Data Engineer Internship at Chistats Labs. Guided by Girish Bamane, Umaima Surti.
SarthakNiwate_week_3
These are tasks completed during Python Data Engineer Internship at Chistats Labs. Guided by Girish Bamane, Umaima Surti.