Grasp Knowledge Science, AI, and Machine Studying with hands-on initiatives in Python, Deep Studying, Large Knowledge, and Analytics
What you’ll study
Perceive Knowledge Science Workflow: Grasp the end-to-end knowledge science lifecycle, from knowledge assortment to mannequin deployment.
Knowledge Assortment Methods: Be taught to assemble knowledge from APIs, databases, and net scraping.
Knowledge Preprocessing: Clear and preprocess uncooked knowledge for evaluation and modeling.
Exploratory Knowledge Evaluation (EDA): Uncover patterns and tendencies in datasets utilizing visualization instruments.
Function Engineering: Create and optimize options to enhance mannequin efficiency.
Machine Studying Fashions: Construct regression, classification, and clustering fashions utilizing scikit-learn.
Deep Studying Methods: Practice neural networks with TensorFlow and PyTorch.
Mannequin Deployment: Serve AI fashions utilizing Flask, FastAPI, and Docker.
Large Knowledge Dealing with: Work with massive datasets utilizing instruments like Hadoop and Spark.
Moral AI Practices: Perceive knowledge privateness, bias mitigation, and AI governance.
English
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