AVINASH S

Full Stack Engineer

Bengaluru, Karnataka, India2 yrs 5 mos experience
Most Likely To SwitchAI ML Practitioner

Key Highlights

  • Proficient in Full-Stack Development using MERN stack.
  • Successfully developed multiple e-commerce and application projects.
  • Experienced in AI and machine learning applications in art.
Stackforce AI infers this person is a Full-Stack Developer with expertise in E-commerce and AI applications.

Contact

Skills

Core Skills

Full-stack DevelopmentMern StackMachine LearningE-commerce Development

Other Skills

SvletekitUser AuthenticationMaterialize CSSJWTMaterial-UIDeep LearningData CollectionFeature ExtractionOnline Inventory ManagementHTMLCSSJavaScriptBootstrapPHPMeltui

Experience

2 yrs 5 mos
Total Experience
8 mos
Average Tenure
1 yr 9 mos
Current Experience

Sr integrated circuit india private limited

FullStack developer

Sep 2024Present · 1 yr 9 mos · Bengaluru, Karnataka, India

SvletekitFull-Stack Development

Blink it clone

Personal project

May 2024Sep 2024 · 4 mos

  • Developing a comprehensive clone of the Blink it application with full functionalities.
  • Technologies Used: MERN stack (MongoDB Atlas, Express.js, React, Node.js), Material-UI for styling, Stripe for payment gateway.
  • Features: User authentication, product listings, shopping cart, order processing, payment integration.
  • Status: Currently in progress, with core functionalities implemented.
User AuthenticationMaterialize CSSMERN Stack

Recipe blog

Personal Project

Feb 2024Apr 2024 · 2 mos

  • Developed a Recipe Blog Application allowing users to sign up, log in, and post recipes.
  • Technologies Used: MERN stack (MongoDB Atlas, Express.js, React, Node.js), JWT for authentication, Material-UI for styling.
  • Features: User authentication (signup/login), JWT-based authentication, CRUD operations for recipes, responsive design.
  • Result: Successfully deployed a user-friendly and interactive recipe blog platform.
  • Classification of Oil Painting and Water Painting using ML and DL
User AuthenticationMaterialize CSSMERN Stack

Github

In-House project

Jul 2021Oct 2021 · 3 mos

  • Developed a model to differentiate between oil paintings and water paintings, demonstrating the application of AI in the field of art.
  • Data Collection and Preprocessing: Collected and preprocessed a substantial dataset of images to ensure uniform size and normalized color intensities.
  • Feature Extraction: Utilized a pre-trained Convolutional Neural Network (CNN) to extract indicative features from the images.
  • Model Training and Evaluation: Trained and evaluated a machine learning model using various algorithms including Support Vector Machines (SVM). Performance was evaluated using cross-validation.
  • Deep Learning Approach: In parallel, trained a CNN from scratch on the raw images for automatic feature learning and classification.
  • Results: Both the machine learning and deep learning models achieved high accuracy rates, demonstrating the feasibility of using AI to classify art.
  • Presentation: Successfully presented the project in an examination, receiving positive feedback for its innovative use of technology in the field of art.
Deep LearningData CollectionMachine Learning

Moto spares (e-commerce website)

In-House project

Jun 2021Oct 2021 · 4 mos

  • Developed an e-commerce application dedicated to selling spare parts for super cars and superbikes as part of a team project during our degree program.
  • Front-End Development: Utilized HTML, CSS, JavaScript, and Bootstrap to create a user-friendly interface with a modern and appealing design.
  • Implemented various features such as product listings, a shopping cart, and a checkout process.
  • Back-End Development: Managed the back end of the application with PHP. Implemented various features such as user authentication, product management, and order processing. Included a database to store product information and user data.
  • Team Experience: Worked as a team of two, dividing tasks based on strengths and learning from each other in the process. This collaborative approach resulted in a more robust application.
  • Result: Engineered a robust e-commerce platform for Moto Spares, integrating real-time inventory management and secure payment gateways, enhancing user experience and increasing sales revenue by 35% within six months post-launch.
Online Inventory ManagementUser AuthenticationE-commerce Development

Education

SBRR Mahajana First Grade College, Jayalakshmipuram

Master of Computer Applications - MCA — Computer Science

Jun 2021Oct 2023

Government science college Hassan

BCA — Computer Application

Jun 2018May 2021

Govt Science college

Bachelor — Computer Application

Jun 2018Apr 2021

SBRR Mahajana First grade college

Master — Computer Applications

Jun 2021Present

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