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Data Scientist
I’m Shivam Shukla, a Data Scientist specializing in AI, Machine Learning, and Generative AI. I build smart solutions using LLMs, Computer Vision, and NLP to turn data into real-world impact. Let’s bri...
À propos de ce service
Hi there! I'm Shivam Shukla, a data scientist and passionate about artificial intelligence, machine learning, and data-driven problem solving.
I specialize in building AI-powered solutions using Large Language Models (LLMs), Generative AI, Computer Vision, and Natural Language Processing (NLP). My goal is to transform raw data into actionable insights and intelligent systems.
What I Offer:
- End-to-end Machine Learning model development and optimization
- Generative AI apps (Chatbots, LLM fine-tuning, Prompt Engineering)
- Computer Vision projects (image classification, object detection)
- NLP tasks (text analysis, summarization, sentiment analysis)
- API & Web App Deployment using Flask or Streamlit
- Data Preprocessing, Exploratory Data Analysis (EDA), and Visualization
️ Tech Stack:
Python | C++ | TensorFlow | PyTorch | Scikit-learn | OpenCV | SQL | MongoDB | Streamlit | Flask
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Langage de programmation:
Python
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SQL
Frameworks:
Scikit-learn
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keras
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PyTorch
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Panda
Outils:
Jupyter Notebook
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opencv
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tensorflow
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MLflow
•
Colab
Mon portfolio
Autres services de Data science et machine learning I Offre
FAQ
Q1: What do you need from me to get started?
To begin your project, I’ll need a clear description of your goal (e.g., prediction, classification, chatbot, etc.), access to any datasets (if available), and any specific requirements such as desired model type or deployment format (Flask API, Streamlit app, etc.).
Q2: Can you help me choose the right AI or ML approach for my problem?
Absolutely! I’ll analyze your problem and recommend the best approach — whether it’s a traditional ML model, a deep learning network, or a Generative AI solution using LLMs.
Q3: Will you explain the model and results after delivery?
Yes! I always provide a brief technical explanation of the model’s working, performance metrics, and results interpretation so you fully understand your AI solution.
Q4: Do you provide documentation and code comments?
Yes — all code is well-documented and includes comments for clarity. I can also provide a README file or report explaining setup and model functionality.
Q5: Do you provide deployment support for the model?
Yes, I can help deploy your trained model as a Flask API or Streamlit web app and even assist with cloud hosting (AWS, Azure, or Google Cloud) if needed.
