kedarvkunte

End-to-End-Data-Science-Project-Time-Series-Analysis-for-Temperature-Forecasting-using-ARIMA-Model

Successfully collected, cleaned and analysed the time series data and used ARIMA model to forecast average temperature using and visualized the Temperature pattern using Python Numpy, Pandas, Matplotlib and Statsmodels

Prediction_with_SVM_on_Tumor_Dataset

Here classification on the tumor dataset is performed using Support Vector Machine. Tumor dataset has nine features and a binary output. Nine features correspond to measurements obtained from medical imaging data. The output labels are logic 1 or 0 and corresponds to the presence or absence of tumor

Data-Visualization-and-State-Prediction-using-Bayesian-Inference-with-Markov-Chain-Monte-Carlo

In this project, the state of the object is predicted using Bayesian Inference Markov Chain Monte Carlo (MCMC) algorithm. For Data visualization, I used Matplotlib to correctly observe the Convergence to Stationary Distribution by plotting Histogram and Bar Charts. Successfully achieved low Mean Squared Error of 0.0003 for various test cases involving prior-posterior probability.

TensorFlow-based-Text-Classification-with-Convolutional-Neural-Networks-Deep-Learning-in-NLP-

Successfully implemented Sentiment Analysis, a Natural Language Processing (NLP) task using TensorFlow, a Deep Learning framework on shallow Convolutional Neural Networks (CNN) architecture

Advanced-SQL-Tableau-Integration-for-Business-Intelligence-on-Large-Database

Successful SQL + Tableau Integration which provides insights into Business Intelligence with the help of SQL queries and visualizing the Data in Tableau to create Dashboard for Employees

SQL-for-Data-Analytics-and-Business-Intelligence-using-MySQL-Workbench

SQL is a standard language for storing, manipulating and retrieving data in databases. It is most commonly used in Data Analytics and Business Intelligence. Here all the SQL queries are written using MySQL WorkBench. Used a big database consisting of many tables to perform operations using various SQL queries.

Understanding-Python-concepts-with-Jupyter-Notebook

Python concepts can be best understood with the help of Jupyter Notebook

CSV-Data-Extraction-and-Exploration_with_Numpy

Successfully carried Exploratory Data Analysis with the help of Numpy module

Gauss_Jordan_Elimination_and_Linear_Regression

The Gauss-Jordan Elimination and Ordinary Least Squares Linear Regression is carried out. Unit tests are provided for testing various test cases. Python libraries used are Numpy, Timeit, Unittest, Sklearn, Matplotlib.

Introduction-to-NLP

Lectures for Udemy - INLP

machine_learning_examples

A collection of machine learning examples and tutorials.

Probability-and-Statistics-with-the-help-of-Python

In this project, the inverse normal Cumulative Distribution Function (CDF), Monte Carlo Expected Value have been implemented with the help of Python functions.

Significant-Memory-Reduction-via-Unsupervised-Learning-with-PCA-and-K-Means-clustering-on-image-data

In this project, unsupervised learning is implemented with the help of python modules. Memory reduction is achieved using image compression via unsupervised learning algorithms.

Basic-Python-Code

My first python code

Debugging-and-Testing-in-Python

Debugging and Testing is carried out with the help of Python.

Getting-Started-with-SAS

Getting-started-with-Tableau

Tableau is an industry leading BI tool that focuses on data visualization, dashboarding and data discovery. It is great tool for visualizing data for the data scientists.

hello-world

First Repository

Introduction_to_Tensorflow

TensorFlow is one of the powerful Deep Learning frameworks.

natural-language-processing

Resources for "Natural Language Processing" Coursera course.

Object-Oriented-Programming-in-Python

Experiencing classes and objects in Python

simulated-unsupervised-tensorflow

TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"

Text-Mining-and-Natural-Language-Processing-with-R

Text Data is everywhere. It is important to get, clean and analyze the data and explore and model it using Natural Language Processing