vijay-gadre Goto Github PK

1_simple_linear_regression

2nd_hand_car_price_prediction

The prices of new cars in the industry are fixed by the manufacturer with some additional costs incurred by the Government in the form of taxes. So, customers buying a new car can be assured of the money they invest to be worthy. But due to the increased price of new cars and the incapability of customers to buy new cars due to the lack of funds, used cars sales are on a global increase (Pal, Arora, and Palakurthy, 2018). There is a need for a used car price prediction system to effectively determine the worthiness of the car using a variety of features. Even though there are websites that offer this service, their prediction method may not be the best. Besides, different models and systems may contribute to predicting power for a used car’s actual market value. It is important to know their actual market value while both buying and selling.

attendance

audio_books_classification

The Data is from an Audiobook App. Logically, it relates to the audio versions of books ONLY. Each customer in the database has made a purchase at least once, that's why he/she is in the database. We want to create a machine learning algorithm based on our available data that can predict if a customer will buy again from the Audiobook company.

bank_loan_prediction

Loans are the core business of banks. The main profit comes directly from the loan’s interest. The loan companies grant a loan after an intensive process of verification and validation. However, they still don’t have assurance if the applicant is able to repay the loan with no difficulties.

barcode_face_attendance

chatvibe-exploring-sentiments-in-whatsapp-chats

codestackr

company-profits-regression

customer_personality_analysis

Customer Personality Analysis is a detailed analysis of a company’s ideal customers. It helps a business to better understand its customers and makes it easier for them to modify products according to the specific needs, behaviors, and concerns of different types of customers.

daily_activity_tracker_ajp_pbl

darknet

Convolutional Neural Networks

deep-learning-keras-tensorflow

Introduction to Deep Neural Networks with Keras and Tensorflow

discord-clone

ds_retention_classification_project

Aims to analyze employee data and build predictive models to identify and mitigate factors that lead to high employee turnover.

hands-on-machine-learning-with-scikit-learn-keras-and-tensorflow

Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

hotel-design2

iphone-demo-design

javascript_pr

karnikakapoor

market_segmentation

mlops-on-gcp

mnist_handwritten_digit_classification

neural_network-chatbot

opencv

Open Source Computer Vision Library

portfolio

portfolio-2

timeless

titanic_survival_prediction

The sinking of the Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the widely considered “unsinkable” RMS Titanic sank after colliding with an iceberg. Unfortunately, there weren’t enough lifeboats for everyone on board, resulting in the death of 1502 out of 2224 passengers and crew. While there was some element of luck involved in surviving, it seems some groups of people were more likely to survive than others. In this challenge, we ask you to build a predictive model that answers the question: “what sorts of people were more likely to survive?”

usa-storm_data_analysis