Skip to content
View farshad257's full-sized avatar
🎯
Focusing
🎯
Focusing

Block or report farshad257

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
farshad257/README.md

Hi, I'm Farshad Tofighi

Applied AI & Machine Learning Engineer | Python, LLMs, AI Automation | UI Developer

I build practical AI systems end to end. My work runs from data exploration and model development to LLM-powered applications, backend services and APIs, automated workflows, and clean, responsive user interfaces.

💫 About Me

I came to AI from geoscience. I hold a degree in Petroleum Engineering (Oil Exploration) from Imam Khomeini International University (IKIU). My research there used artificial intelligence and 3D seismic attributes to estimate reservoir porosity. That work taught me how to turn noisy, complex real-world data into reliable models people can base decisions on, and I bring the same approach to every project.

Today I work across machine learning, deep learning, natural language processing, and computer vision. I like taking a problem from raw data to a working solution: cleaning and analyzing data, building and evaluating models, explaining their behavior, and fitting them into real workflows.

To put models into production, I build backend services and REST APIs with FastAPI, Django, and Django REST Framework. That covers serving ML and LLM models through fast, well-documented endpoints, as well as building full Django backends with data models, authentication, and business logic.

I also design AI-driven automation workflows with Python and n8n. These workflows connect LLMs, APIs, and business tools so repetitive processes can run on their own.

My front-end development skills (HTML, CSS, JavaScript) let me build responsive, visually engaging interfaces with modern animations. Together with my backend skills, this means I can deliver the whole product: the model, the API that serves it, and the interface people use.

I also teach Python programming and artificial intelligence at the Shahriar branch of the Technical and Vocational Training Organization (TVTO) in Tehran. There I help learners move from fundamentals to hands-on AI projects.

📊 Featured Projects

LLMs & AI Automation

Describe Image in Persian · Live Demo Upload an image and get a Persian-language AI description, with optional speech output. Built on GPT-4o vision and a Gradio interface, and deployed as a Hugging Face Space. Python GPT-4o Gradio Multimodal AI TTS

TTS Workflow An AI-powered text-to-speech automation workflow built on an OpenAI-compatible API, with a Gradio front end for easy use. Python Gradio OpenAI API Automation

Deep Learning & Computer Vision

Facial Emotion Recognition (FER-2013) A 5-layer CNN that recognizes human emotions from facial images. It uses data augmentation, max pooling, and dropout, and reaches 76% validation / 63% test accuracy on FER-2013. Useful for human-computer interaction. Python CNN Deep Learning Computer Vision

Handwritten Digit Recognition A CNN classifier for handwritten digits, written to PEP 8, clean-code, and SOLID principles. It includes a case study comparing the performance of simple and complex models. Python CNN Clean Code Model Comparison

Machine Learning & NLP

Income Forecasting with Stacked Ensembles A stacked ensemble regressor that combines Gradient Boosting, AdaBoost, Bagging, Linear Regression, and Decision Trees. It reaches R² = 0.876. Python scikit-learn Ensemble Learning Regression

Sentiment Analysis on IMDB A Bernoulli Naive Bayes model that reaches 94% accuracy on IMDB movie-review sentiment classification. It shows how far a well-prepared simple model can go. Python NLP Text Classification NLTK

Energy Consumption Modeling Time-series forecasting of energy consumption. The project covers data preparation, feature engineering, outlier detection, and model evaluation. Python Time Series Feature Engineering Forecasting

🧑🏻‍💻 What I Work On

  • Applied Machine Learning: predictive modeling, feature engineering, model evaluation, and explainability
  • Deep Learning: neural networks for vision and language tasks
  • NLP & LLMs: text processing, Transformer models, and LLM-based applications
  • Computer Vision: image analysis and recognition
  • Backend & APIs: REST APIs and model-serving services with FastAPI, full backends with Django and Django REST Framework
  • AI Automation: end-to-end workflows that combine LLMs, APIs, and webhooks
  • UI Development: responsive, animated, user-focused web interfaces

💻 Tech Stack

Area Tools
Languages Python JavaScript HTML5 CSS3
Machine Learning scikit-learn PyCaret SHAP
Deep Learning PyTorch TensorFlow
NLP & LLMs Hugging Face Transformers NLTK OpenAI API
Data & Visualization NumPy Pandas Matplotlib Seaborn Plotly
Backend & APIs FastAPI Django Django REST Framework REST API Design
Automation & Apps n8n Gradio REST APIs Webhooks

🌐 Socials:

Instagram LinkedIn email

Popular repositories Loading

  1. Regrassion_Income_Forcasting Regrassion_Income_Forcasting Public

    A powerful stacked ensemble model for income prediction, combining GradientBoosting, AdaBoost, Bagging, Linear Regression, and Decision Trees. Achieves an impressive R² of 0.8761 on the RoS_sample_…

    Jupyter Notebook 1

  2. Simple_Paint Simple_Paint Public

    It's a simple python code with GUI that created by tkinter library and convert to .exe file.

    Python

  3. CNN_FER-2013 CNN_FER-2013 Public

    A 5-layer CNN model for facial emotion recognition trained on FER-2013. Achieved 76% validation and 63% test accuracy using data augmentation. Key features include convolutional layers, max pooling…

    Jupyter Notebook

  4. NLP_IMDB NLP_IMDB Public

    A simple Bernoulli Naive Bayes model achieved 94% accuracy on the IMDB sentiment analysis task. Despite its simplicity, it performed exceptionally well.

    Jupyter Notebook

  5. farshad257 farshad257 Public

  6. Hand_writing_digits Hand_writing_digits Public

    Designing a CNN model to recognize and classify Hand writing digits in English. Actually this is designed based on PEP8, clean code and SOLID principle. Also this code is designed to compare perfor…

    Python