cskarthik93@gmail.com's repositories
PythonBootcamp
Python 3 - the latest version of Python PyCharm, Jupyter Notebook, Google Colab Python Scripting and Automation Python Game Development Web Scraping Beautiful Soup Selenium Web Driver Request WTForms Data Science Pandas NumPy Matplotlib Plotly Scikit learn Seaborn Turtle Python GUI Desktop App Development Tkinter Front-End Web Development HTML 5 CSS 3 Bootstrap 4 Bash Command Line Git, GitHub and Version Control Backend Web Development Flask REST APIs Databases SQL SQLite PostgreSQL Authentication Web Design Deployment with GitHub Pages, Heroku and GUnicorn
BAFundamentals
Fundamentals in Business Analytics
cskarthik93.github.io
Personal Portfolio
Data-Science-Methodology
Share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand.
DataAnalysisWithPython
Packages for Data Science, Basic Insights from Data, Data Wrangling, Exploratory Data Analysis, Prediction & Decision Making, Model Development, Selection, Evaluation & Refinement
DataVisualizationUsingPython
Using python libraries such as Matplotib, Seaborn and Folium for the creation and customization of graphical representation outputs for both small and large-scale data sets.
DataVizWithTableau
Visualization of Data with Tableau & D3
DeepLearning
Deep Learning & its Models, Deep Learning Platforms and Software Libraries, TensorFlow, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Restricted Boltzmann Machine, Autoencoders, Hardware Accelerated Deep Learning, Deep Learning in the Cloud, Distributed Deep Learning
MachineLearningWithPython
Popular algorithms: Regression, Classification, and Clustering, Market Basket Analysis, Recommender Systems: Content-Based, Collaborative Filtering, Hybrid Filtering & Popular models: Train/Test Split, Gradient Descent, and Mean Squared Error
NY311-CapstoneProject1
The people of New Yorker use the 311 system to report complaints about the non-emergency problems to local authorities. Various agencies in New York are assigned these problems. The Department of Housing Preservation and Development of New York City is the agency that processes 311 complaints that are related to housing and buildings. In the last few years, the number of 311 complaints coming to the Department of Housing Preservation and Development has increased significantly. Although these complaints are not necessarily urgent, the large volume of complaints and the sudden increase is impacting the overall efficiency of operations of the agency. Therefore, the Department of Housing Preservation and Development has approached your organization to help them manage the large volume of 311 complaints they are receiving every year. The agency needs answers to several questions. The answers to those questions must be supported by data and analytics. These are their questions: Which type of complaint should the Department of Housing Preservation and Development of New York City focus on first? Should the Department of Housing Preservation and Development of New York City focus on any particular set of boroughs, ZIP codes, or street (where the complaints are severe) for the specific type of complaints you identified in response to Question 1? Does the Complaint Type that you identified in response to question 1 have an obvious relationship with any particular characteristic or characteristics of the houses or buildings? Can a predictive model be built for a future prediction of the possibility of complaints of the type that you have identified in response to question 1? Your organization has assigned you as the lead data scientist to provide the answers to these questions. You need to work on getting answers to them in this Capstone Project by following the standard approach of data science and machine learning.
PowerBI-AdventureWorks
Connecting & Shaping Data; Relational Data Modelling; data analysis expressions (DAX);Visualizing Data with Reports
PythonForDataScience
Python Essentials, API, IBM Watson etc.
TagMyNews-Classification
Labelled Dataset - Classification of News using Multinomial Naive Bayes, Neural Networks with SoftMax Layer & SVM