Naveen A's Projects
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.
Feature Engineering, Data Exploration and Visualization project based on 911 emergency calls data from Kaggle.
Classification of bank customers using Decision Tree Classifier and Logistic Regression. Data Visualization, Exploratory Data Analysis, model building and evaluation.
Prediction of HVAC System Electricity Consumption. Data Visualization, Data Pre-processing and Regression Model building. Data obtained from Lawrence Berkeley National Laboratory.
Basics of Spark an Pyspark to handle RDD (Resilient Distributed Datasets) (Big Data).
Predict hourly bike rental demand using Decision Tree Regressor and Linear regression. Data Visualization, model building, Regression, Exploratory data analysis.
Cheat Sheets that I use for git, Python, SQL, Data Science, Deep Learning, Machine Learning, Data visualization and Statistical Analysis.
Clustering colleges using K-Means Algorithm into Private and Public colleges using the Features.
Data Science Repository.
Cancer prediction project with deep learning using classification along with early stopping callback and dropout layer
House Price Prediction based on Features using Deep learning Neural Networks.
This is a demo repo for the python in 30 days class.
Code for the online course "Deployment of Machine Learning Models"
Linear Regression Project to find out which variable has the greatest effect on the yearly amount spent by customers of an ecommerce retailer.
Python Codes. Google Colab essential codes, data visualization, outlier treatment.
Data Science regression project with web-scapper, data cleaning, feature engineering, Exploratory Data Analysis, Model building, optimization, evaluation and model productionization.
When a List of internet article URLs are provided this program returns a .csv file with the Article Headings and Body.
SVM Classifier Project for classifying the right 'species' - Target Label for the Features of Flowers using the super famous 'Iris' dataset.
Contains Files and Data which were used in submissions for Kaggle Titanic - "Machine Learning from Disaster" Competition.
Practice project for K-Nearest-Neighbors Classifier.
Classification project using Tensorflow-keras (deep learning) to determine is a customer got Loan or not.
Classification project using Decision Tree Classifier and Random Forest Classifier to classify whether the Loan was fully paid or not.
Recommender System for movies according to Rating provided by users.
Config files for my GitHub profile.
Spam detection model for predicting whether SMS text is Spam or not.