Hi, I'm Sid! 👋

🚀 About Me

"I am a dedicated Computer Vision Engineer. My expertise lies in leveraging algorithms and machine learning to derive valuable insights from complex datasets. Passionate about the limitless possibilities at the intersection of technology and human understanding, I am actively working towards becoming a full-stack Data Scientist. In my current role, I contribute to the entire computer vision pipeline – from meticulous data preprocessing to effective model deployment. Eager to further expand my skills and make meaningful contributions."

🛠 Skills

Programming Languages:

Python (proficient)

Web Frameworks:

Flask (experience in building web applications) Streamlit (creating interactive and data-driven web applications)

Machine Learning:

Building end-to-end machine learning projects Deep learning expertise

Computer Vision:

Implementing computer vision techniques and algorithms

Data Processing:

Preprocessing and transforming raw data for analysis

Pipeline Development:

Designing and implementing efficient data pipelines

Model Deployment:

Deploying machine learning models for real-world applications

Database Management:

Experience with databases, including MySQL, for data storage, retrieval, and managemen

Data Visualization:

Skills in creating meaningful visualizations to communicate insights effectively

Statistical Analysis:

Knowledge of statistical techniques for data analysis and model evaluation

Cloud Computing:

Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) for scalable and efficient computing

My Journey

Studied Psychology, earning a Bachelor's and Master's degree in Clinical Psychology.

Worked as a clinical psychologist, gaining hands-on experience in mental health support.

Discovered the potential of AI in improving mental health applications.

Acquired skills in data science, machine learning, and computer vision.

Passionate about the positive impact of AI-human collaboration, especially in mental health.

Aspiring to become a full-stack Data Scientist for a broader impact.

siddharthiyervarma's Projects

-deepsonar_classifier-

The primary objective of this project is to design and train a deep neural network that can generalize well to new, unseen data, effectively distinguishing between rocks and metal cylinders based on the sonar chirp returns.

automated-pneumonia-predicter

This project focuses on leveraging deep learning techniques to predict lung disease, specifically pneumonia, from chest X-ray images.

awesome-generative-ai_ideas

A curated list of modern Generative Artificial Intelligence projects and services

bank-note-classification

This project focuses on the classification of banknotes using various supervised machine learning models. The primary objective is to develop a robust system that can accurately distinguish between genuine and counterfeit banknotes based on a set of features.

breast-cancer

ML project Detcting Canverous Cells

cnn-mnist

The aim was to develop a robust Convolutional Neural Network (CNN) for accurately classifying handwritten digits from the MNIST dataset

live_covid_report_berlin

Develop a dynamic COVID-19 dashboard for Berlin districts, providing daily updates on key metrics like 7-day-incidence, rolling averages, and raw case counts. Users can compare specific districts using official Berlin government data from berlin.de, offering a user-friendly tool for monitoring district-level COVID-19 trends in Berlin.

loan-approval-prediction

leverage decision tree-based models for predicting credit approval.

web_scarping_book_store

Introduction: The "Bookstore Analytics" project involves the analysis of a dataset containing information about books available in an online bookstore. A web scraping application was build for this

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