Prankur Shukla's Projects
In this Regression project we extracted the data related to Air Quality Index from a Website. We have pre-processed the extracted data and made predictions on the AQI based on other factors. We have solved this problem by different algorithms along with Hyper Parameter Tuning.
In this project we have created a Artificial Neural Network to classify the audios along with Exploratory Data Analysis and Data Preprocessing.
In this Regression Machine Learning Project, we will be analysing the used car dataset taken from a website www.cardekho.com, consisting of features like car name, manufacturing year, kms driven, ownership, torque, fuel type etc. Our focus will be on analysing the data, getting the insights related to these features and there role in affecting the sales price, we will perform feature engineering, feature selection and develop a Regression model that will predict the sales price based on the new test data.
In this Classification Machine Learning Project, we will be analysing the dataset taken from www.kaggle.com related to details of credit card owners. This data consists of features like Gender, Income type, House type, marital status and many more. Our focus will be on analysing the data, getting the insights related to these features and there role in affecting the target, we will perform feature engineering, feature selection and develop a Classification model that will predict whether it is a Fraud or not based on the new data.
Face Recognition Application developed by transfer learning technique (VGG16) on data collected by a feed from a webcam.
In this project, we will be creating a Fake news classifier model that will classify the news based on the 'title' and 'text', whether it is 'Real' or 'Fake'. The dataset that we are using here is taken from www.kaggle.com.
This project is basically a Exploratory Data Analysis on Google Play Store Apps Data in order to draw several useful insights and leverage these insights to perform better as compared to other applications.
In this Classification Machine Learning Project, we will be analysing the dataset taken from www.kaggle.com related to details of patients. This data consists of features like age, sex, chest pain type, blood pressure and many more. Our focus will be on analysing the data, getting the insights related to these features and there role in affecting the target, we will perform feature engineering, feature selection and develop a Classification model that will predict whether the patient has a heart disease or not.
In this project we will apply Recurrent Neural Network (LSTM) which is best suited for time-series and sequential problem, we will be creating a LSTM model, train it on data and make predictions to check its performance.
My Introduction and Future Goals.
Security Camera application to record the feed if any body or face is detected by using OpenCV in python.
In this project we have created a spam classifier model on UCI dataset. We performed data cleaning and preprocessing, followed by Stemming and Bag of Words technique and finally developed a Naive Bayes Multinomial model.
In this project we will be creating a RandomForestClassifier model that will be able to predict the movement of the stock based on the news headlines, here we are using a dataset taken from www.kaggle.com.
This a EDA (Exploratory Data Analysis) project on a personal Whatsapp Group Chat inorder to obtain some insights and understand the group chat behaviour. There can be number of questions that a person can think like who messages the most, busiest hours in chat, busiest month of chat, mostly used emojis..... and many more, it solely depends on your imagination.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent