SACHIN

EDUCATION

Sultanpur,( U.P) India Kamla Nehru Institute Of Technology Aug 2017 – June 2021

Bachelor Of Technology Electronics Engineering CGPA: 6.71 SKILLS

Machine Learning : Python, SQL, Tensorflow, NumPy, Matplotlib, Pandas, Scikit-learn

Web Development: HTML5, CSS3, BootStrap4, JavaScript, React.js, Node.js, MongoDB

Programming language and Strong Area: C++, Data Structure and Algorithms, Basic Java

Version Control Tool: Git and GitHub

TECHNICAL PROJECTS

Netflix Clone React, Firebase (Firestore & authentication), Compound &Styled components

• It’s a Netflix Clone which has multiple pages: Home, browse (which uses Firebase Authentication), sign in, sign up and Firebase database is used to store user's data.

• Fuse.js library has been used for live search to browse movies, web series etc. React Router is used to navigate through different pages.

• Each movie or web series has been attached with a small length video and Firestone has been used as a database.

WhatsApp Web Clone React, MongoDB, Node.js, Firebase January 2020 – Present

• It’s a messaging web app like WhatsApp web, registering with Email id and has one to one and group chat option. Pusher.js library is used to give Real-time functionality.

• The frontend has been designed with React and MongoDB is used as a database.

• Firebase is used to deploy this webpage.

• MERN Stack is used to developing this webpage.

Credit Card Fraud Detection Model Python, NumPy, Pandas, Matplotlib, SciKit learn, Seaborn

• Model which tries to predict that whether a transaction is a fraudulent or not based on various variables.

• Dataset has been taken from Kaggle.com.

• Model has been trained with isolation forest algorithm, Local Outlier factor algorithms, Random forest algorithm and logistic regression for better accuracy.

Students Details Recorder Python, Library- Tkinter Feb 2019 – March 2019

• GUI application which takes the input of details of students and stores all the data in CSV file format.

• Tkinter library is used to give a graphical user interface to this application.

Titanic Dead / Alive Model Python, NumPy, Pandas, Matplotlib Nov 2019 – Dec 2019

• ML model which predicts whether the person would have been saved or not based on different factors like age, male/female, reservation class etc.

• Dataset has been taken from Kaggle.com, wrangled to bool values.

• All the blank values have been cleaned and the model has been trained with Logistic regression. COURSES

SQL for Data Science specialization from University of California.

Angela yu Udemy course on Full Stack Web Development.

Data Structures and Algorithms specialization from University of California San Diego.

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