🚀 Roadmap to Become a Machine Learning Engineer 💻

📂 Programming Basics
 ∟📂 Master Python & OOP
  ∟📂 Learn Data Structures & Algorithms
   ∟📂 Master Git & Version Control

📂 Mathematics for ML
 ∟📂 Linear Algebra & Calculus
  ∟📂 Probability & Statistics
   ∟📂 Optimization Techniques

📂 Data Handling & Processing
 ∟📂 Work with Pandas & NumPy
  ∟📂 Data Cleaning & Preprocessing
   ∟📂 Feature Engineering & Selection

📂 Machine Learning Fundamentals
 ∟📂 Understand Supervised & Unsupervised Learning
  ∟📂 Master Scikit-Learn & ML Algorithms
   ∟📂 Model Training, Evaluation & Tuning

📂 Deep Learning & Neural Networks
 ∟📂 Learn TensorFlow & PyTorch
  ∟📂 Build & Train Neural Networks
   ∟📂 Master CNNs, RNNs & Transformers

📂 ML System Deployment
 ∟📂 Learn Model Deployment (Flask, FastAPI)
  ∟📂 Work with MLOps & Cloud Platforms
   ∟📂 Deploy Models to Production

📂 Projects & Real-World Applications
 ∟📂 Build End-to-End ML Projects
  ∟📂 Work on Open-Source Contributions
   ∟📂 Showcase on GitHub & Kaggle

📂 Interview Preparation & Job Hunting
 ∟📂 Solve ML Coding Challenges
  ∟📂 Learn System Design for ML
   ∟📂 Network & Apply for Jobs

✅️ Get Hired

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