Hi I'm
Sajawal Hassan
A Web Developer / Data Scientist
Innovative Mindset
Critical Thinker
Hi, I'm Sajawal Hassan.
I'm a teenage guy who loves working in the tech industry. I've built many projects in many different fields from Website Development to Game Development to Data Science.
I have always had a passion for tech since I was young, starting my coding journey at the young age of 8. I started with Website Development and went on to learn many different fields. As of now I am extremely experienced in Website Development, and quite experienced with Data Science. Because of Website Development, I am also very well versed in App Development, having learnt React Native. I have made multiple projects through React Native as well (although unfinished)
I can give you the results you need, with having built multiple full stack projects from a Reddit Clone to a Discord Clone and to even a Google Clone, I know for a fact I can do the task required of me. I have also created the website for an event of one of the the biggest universities in my home town Pakistan, called CRSOM, I have multiple projects of React Native with fullstack expertise. Along with all this I've learnt quite a lot of Data Science as well, from creating an LSTM that generates sentences to a sentiment analysis LSTM. I've also created GANS capable of generating images.
All in all, I am someone who will be very valuable to you and your team, with my skills, I am confident I can make your dreams into a digital reality.
Name
Sajawal Hassan
sajawalhassan.1feb@gmail.com
Employment
Open
ReactJS
React Native
Expo
NextJS
TailwindCSS
React Query
Prisma
Rest APIs
Git / Github
SQL
MongoDB
HTML5
CSS3
Javascript
Typescript
Django
Projects
This project is a Reddit clone developed using NextJS 14, Typescript 5, Prisma ORM 5, and Tailwind CSS 3. It aims to replicate some of the core functionalities of the popular social media platform Reddit.
This project is a Discord clone created using a modern tech stack including NextJS 13, Typescript 5, Prisma ORM 5, and Tailwind CSS 3. It aims to imitate the key features of Discord. There is no live demo sine I am using web sockets so to host it would require me to pay.
This project is a Google clone created using ReactJS and Firebase. It uses the google api to make a fully working search engine.
This project was made for a university to handle registrations for a national event called CRSOM. It was hosted in Pakistan.
ReactJS
React Native
Expo
NextJS
TailwindCSS
React Query
Prisma
Rest APIs
Git / Github
SQL
MongoDB
HTML5
CSS3
Javascript
Typescript
Django
This project is a Reddit clone developed using NextJS 14, Typescript 5, Prisma ORM 5, and Tailwind CSS 3. It aims to replicate some of the core functionalities of the popular social media platform Reddit.
This project is a Discord clone created using a modern tech stack including NextJS 13, Typescript 5, Prisma ORM 5, and Tailwind CSS 3. It aims to imitate the key features of Discord. There is no live demo sine I am using web sockets so to host it would require me to pay.
This project is a Google clone created using ReactJS and Firebase. It uses the google api to make a fully working search engine.
This project was made for a university to handle registrations for a national event called CRSOM. It was hosted in Pakistan.
This project is a Reddit clone developed using NextJS 14, Typescript 5, Prisma ORM 5, and Tailwind CSS 3. It aims to replicate some of the core functionalities of the popular social media platform Reddit.
This project is a Discord clone created using a modern tech stack including NextJS 13, Typescript 5, Prisma ORM 5, and Tailwind CSS 3. It aims to imitate the key features of Discord. There is no live demo sine I am using web sockets so to host it would require me to pay.
This project is a Google clone created using ReactJS and Firebase. It uses the google api to make a fully working search engine.
This project was made for a university to handle registrations for a national event called CRSOM. It was hosted in Pakistan.
Python
Pandas
Numpy
Matplotlib
Tensorflow
Pytorch
Linux
Linear Algebra
Statistics
Projects
This is a DCGAN implementation of generating anime face images using PyTorch, comprising of a generator and discriminator, trained on a dataset of 63,000 anime face images.
This project develops a TensorFlow-based LSTM model for completing sentences. It features a multi-layered architecture with dense layers, an LSTM layer, and a softmax output layer, and is trained using categorical crossentropy and the Adam optimizer.
The project employs LSTM neural networks in Python (PyTorch) for sentiment analysis of text data (reviews). It tokenizes text, constructs LSTM models, and requires common Python libraries for execution.
A digit classifier project utilizing CNNs for hand-drawn number recognition. Built with Python, Matplotlib, Numpy, and TensorFlow. Contains a Jupyter notebook for easy access and aims to expand with a website. Contributions welcome under MIT License.
This is a DCGAN implementation of generating anime face images using PyTorch, comprising of a generator and discriminator, trained on a dataset of 63,000 anime face images.
This project develops a TensorFlow-based LSTM model for completing sentences. It features a multi-layered architecture with dense layers, an LSTM layer, and a softmax output layer, and is trained using categorical crossentropy and the Adam optimizer.
The project employs LSTM neural networks in Python (PyTorch) for sentiment analysis of text data (reviews). It tokenizes text, constructs LSTM models, and requires common Python libraries for execution.
A digit classifier project utilizing CNNs for hand-drawn number recognition. Built with Python, Matplotlib, Numpy, and TensorFlow. Contains a Jupyter notebook for easy access and aims to expand with a website. Contributions welcome under MIT License.
This is a DCGAN implementation of generating anime face images using PyTorch, comprising of a generator and discriminator, trained on a dataset of 63,000 anime face images.
This project develops a TensorFlow-based LSTM model for completing sentences. It features a multi-layered architecture with dense layers, an LSTM layer, and a softmax output layer, and is trained using categorical crossentropy and the Adam optimizer.
The project employs LSTM neural networks in Python (PyTorch) for sentiment analysis of text data (reviews). It tokenizes text, constructs LSTM models, and requires common Python libraries for execution.
A digit classifier project utilizing CNNs for hand-drawn number recognition. Built with Python, Matplotlib, Numpy, and TensorFlow. Contains a Jupyter notebook for easy access and aims to expand with a website. Contributions welcome under MIT License.
Python
Pandas
Numpy
Matplotlib
Tensorflow
Pytorch
Linux
Linear Algebra
Statistics