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The Full Stack Machine Learning course will guide you through the entire machine learning pipeline, from understanding data to building advanced ML models and deploying them in real-world applications. You will gain proficiency in Python, deep learning, model evaluation, and cloud deployment, and work with real-world datasets using tools like TensorFlow and PyTorch.
What you will learn?
- Learn how perspective works and how to incorporate it into your art
- Learn and apply industry-standard drawing techniques
- What is Lorem Ipsum? Lorem Ipsum is simply dummy text of the printing and typesetting
- Learn how perspective works and how to incorporate it into your art
- Learn and apply industry-standard drawing techniques
- What is Lorem Ipsum? Lorem Ipsum is simply dummy text of the printing and typesetting
Requirements
- Master model evaluation and hyperparameter tuning.
- Work on real-world end-to-end ML projects from data cleaning to deployment.
- Deploy ML models in production environments using cloud platforms.
- Learn key machine learning algorithms and techniques (Supervised, Unsupervised, and Deep Learning).
- Build and train machine learning models using libraries like scikit-learn, TensorFlow, and PyTorch.
Features
- Software developers looking to add machine learning skills to their portfolio.
- Professionals transitioning to machine learning from data analytics or engineering.
- Aspiring Machine Learning Engineers or Data Scientists.
- Students who want to specialize in machine learning or AI.
Target audiences
- Interactive discussions and quizzes.
- Capstone project for practical application of skills learned.
- Hands-on coding exercises and mini-projects.
- Learn to deploy machine learning models using cloud-based solutions like AWS or Google Cloud.
- In-depth coverage of machine learning and deep learning concepts.
