Data science/ML/AI@datascience_bds P.1033

DATASCIENCE_BDS Telegram 1033

Data science/ML/AI

✅ Complete AI (Artificial Intelligence) Roadmap 🤖🚀

1️⃣ Basics of AI
🔹 What is AI?
🔹 Types: Narrow AI vs General AI
🔹 AI vs ML vs DL
🔹 Real-world applications

2️⃣ Python for AI
🔹 Python syntax & libraries
🔹 NumPy, Pandas for data handling
🔹 Matplotlib, Seaborn for visualization

3️⃣ Math Foundation
🔹 Linear Algebra: Vectors, Matrices
🔹 Probability & Statistics
🔹 Calculus basics
🔹 Optimization techniques

4️⃣ Machine Learning (ML)
🔹 Supervised vs Unsupervised
🔹 Regression, Classification, Clustering
🔹 Scikit-learn for ML
🔹 Model evaluation metrics

5️⃣ Deep Learning (DL)
🔹 Neural Networks basics
🔹 Activation functions, backpropagation
🔹 TensorFlow / PyTorch
🔹 CNNs, RNNs, LSTMs

6️⃣ NLP (Natural Language Processing)
🔹 Text cleaning & tokenization
🔹 Word embeddings (Word2Vec, GloVe)
🔹 Transformers & BERT
🔹 Chatbots & summarization

7️⃣ Computer Vision
🔹 Image processing basics
🔹 OpenCV for CV tasks
🔹 Object detection, image classification
🔹 CNN architectures (ResNet, YOLO)

8️⃣ Model Deployment
🔹 Streamlit / Flask APIs
🔹 Docker for containerization
🔹 Deploy on cloud: Render, Hugging Face, AWS

9️⃣ Tools & Ecosystem
🔹 Git & GitHub
🔹 Jupyter Notebooks
🔹 DVC, MLflow (for tracking models)

🔟 Build AI Projects
🔹 Chatbot, Face recognition
🔹 Spam classifier, Stock prediction
🔹 Language translator, Object detector

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342 viewsDec 10 at 08:45

tgoop.com/datascience_bds/1033

Create: 2025-12-10
Last Update: 2025-12-11 12:21:02

✅ Complete AI (Artificial Intelligence) Roadmap 🤖🚀

1️⃣ Basics of AI
🔹 What is AI?
🔹 Types: Narrow AI vs General AI
🔹 AI vs ML vs DL
🔹 Real-world applications

2️⃣ Python for AI
🔹 Python syntax & libraries
🔹 NumPy, Pandas for data handling
🔹 Matplotlib, Seaborn for visualization

3️⃣ Math Foundation
🔹 Linear Algebra: Vectors, Matrices
🔹 Probability & Statistics
🔹 Calculus basics
🔹 Optimization techniques

4️⃣ Machine Learning (ML)
🔹 Supervised vs Unsupervised
🔹 Regression, Classification, Clustering
🔹 Scikit-learn for ML
🔹 Model evaluation metrics

5️⃣ Deep Learning (DL)
🔹 Neural Networks basics
🔹 Activation functions, backpropagation
🔹 TensorFlow / PyTorch
🔹 CNNs, RNNs, LSTMs

6️⃣ NLP (Natural Language Processing)
🔹 Text cleaning & tokenization
🔹 Word embeddings (Word2Vec, GloVe)
🔹 Transformers & BERT
🔹 Chatbots & summarization

7️⃣ Computer Vision
🔹 Image processing basics
🔹 OpenCV for CV tasks
🔹 Object detection, image classification
🔹 CNN architectures (ResNet, YOLO)

8️⃣ Model Deployment
🔹 Streamlit / Flask APIs
🔹 Docker for containerization
🔹 Deploy on cloud: Render, Hugging Face, AWS

9️⃣ Tools & Ecosystem
🔹 Git & GitHub
🔹 Jupyter Notebooks
🔹 DVC, MLflow (for tracking models)

🔟 Build AI Projects
🔹 Chatbot, Face recognition
🔹 Spam classifier, Stock prediction
🔹 Language translator, Object detector

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