Pushpendra9350

Pushpendra9350

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Location:India

Home Page:https://indeepdata.com

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Pushpendra9350

Config files for my GitHub profile.

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Task-Manager-With-Node-Js

This is a simple webpage build with NodeJs and JavaScript. In this app we can create new assignments and notes to each assignment.

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DRF-Authentication-API-with-JWT

This is a complete backend API based application which contains Custom User Model, User Registration API, User Authentication/Login API, Get User Profile API, Send Password Reset Email API, Change Password API.

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Option-trading-platform-with-Django

Here we can place trades in real-time with exit variable quantity, add quantity, and can see real-time profit and loss. Technologies used are Python, Django, Django channels for WebSocket, Redis cache, celery for background tasks, Html, JavaScript, Css, Sqlite database.

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Data-Analysis-Notebooks

Data Analysis on various datasets to get better understanding of things in analysis

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Email-verification-with-django

Here we are sending an email to the user's registered email and then user have to verify email before login. If user try to login before verifying then it prompts to first verify email. after verification user able to use application.

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Food-ordering-website-with-Django

This is Food ordering website where we can register, login as restaurant and customer and also we can order food as a customer and can see all of our previous orders.

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Blog-website-for-job-opening-with-Django

This is a demo website for the blog posts for a job portal. Here we can create, update, delete, and also can read the blogs. Technologies used to make this website are Python, Django framework, Html, Css, Sqlite, PostgreSQL, Heroku, and Tools are used Chrome Browser and VS code studio.

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Iris-flower-classification-with-EDA

This is a very simple model to predict Iris flower species. we have three types of species in it (Versicolor, Verginica, Setosa).

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Credit-Cards-Lead-Prediction-for-Bank

This is a web-based application that predicts whether a customer will accept a credit card offer from a bank or not. The accuracy of this model is 87.29%.

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Voice-Recognition-for-Punjabi-singer-Android-app

This is an Android application in which we have to record a song for 10 seconds and this will recognize the voice and tells you the singer's name. The uniqueness of this Case study id it works with regional songs (Punjabi language)

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Sentiment-prediction-on-reviews

This is a single webpage application in which we need to enter a review and this will tell you whether the review is positive or not. To make this work NLP techniques and Logistic regression algorithm is used with 94% accuracy

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Stackoverflow-Tag-Predictor

This is a web-based application in which we are solving a Multilabel classification problem. Here we need to enter the StackOverflow question title and description and it will predict tags for the questions.

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Digit-Recognizer-Android-App-With-AWS

This is a complete Android application to recognize handwritten digits. Model is trained on CNN with 99.19% accuracy. We can further train this model with new data from application itself.

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Inquiry-Response-System-with-Laravel-PHP

This is an application build with Laravel framework and PHP. Here we can create a query and then the admin will reply accordingly.

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