Building a strong AI portfolio isn’t just about showing code – it’s about proving your ability to solve real-world problems. If you’re starting your journey or looking to strengthen your profile, here are Top 5 AI projects you should consider 👇
1️⃣ Chatbot with LLM Integration 🤖
- Build a chatbot powered by GPT-based APIs or open-source models (like LLaMA, Mistral, Falcon).
- Showcase how it handles context retention, multi-turn conversations, and domain-specific tasks.
- Skills Highlighted: NLP, prompt engineering, API integration, deployment.
🔗 Explore: HuggingFace Transformers + LangChain.
2️⃣ Computer Vision Image Classifier 📸
- Train a deep learning model (CNNs, Vision Transformers) to classify images (e.g., plant diseases, fashion items, or X-rays).
- Push it further by adding explainability (Grad-CAM, SHAP).
- Skills Highlighted: Computer vision, PyTorch/TensorFlow, model interpretability.
🔗 Explore: FastAI & Kaggle datasets.
3️⃣ Recommendation System 🎯
- Build a system like Netflix/Spotify/Amazon recommendations.
- Use collaborative filtering + deep learning embeddings to make it smarter.
- Skills Highlighted: Machine learning, data pipelines, personalization algorithms.
🔗 Explore: TensorFlow Recommenders.
4️⃣ AI-Powered Resume Screener / Job Matcher 💼
- Automate screening resumes using NLP & match them to job descriptions.
- Add features like skill extraction, ranking candidates, and bias detection.
- Skills Highlighted: NLP, information retrieval, applied ML in HR-tech.
🔗 Explore: SpaCy + Sentence Transformers.
5️⃣ AI for Finance – Stock Market Sentiment Analysis 📊
- Collect data from news articles, tweets, Reddit posts.
- Train a sentiment analysis model & backtest with stock price trends.
- Skills Highlighted: Text mining, sentiment analysis, time series forecasting.
🔗 Explore: FinBERT & Alpaca API for stock data.
💡 Pro Tip:
- Document everything on GitHub with READMEs.
- Write a LinkedIn post/blog explaining each project.
- Deploy on Streamlit or HuggingFace Spaces for recruiters to test live.
🔥 Start small, go deep, and always align projects to real-world applications. That’s how you stand out in AI hiring!
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