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Data Science & Machine Learning Bootcamp with Python
Python for Scientific Computing & Data Analysis
Python Foundations: Data Structures, List Comprehensions & Functions
(18:42)
Numerical Operations with NumPy Arrays & Matrix Mathematics
(11:40)
Statistical Visualizations with Matplotlib and Seaborn
(17:52)
Data Wrangling & Feature Engineering with Pandas
Data Cleaning: Handling Missing Values, Outliers & Data Imputation
(11:25)
Grouping, Aggregations & Pivot Tables for Business Insights
(12:25)
Feature Engineering: Encoding Categoricals & Scaling Techniques
(22:52)
Supervised & Unsupervised Machine Learning
Linear & Logistic Regression: Model Training & Evaluation
(22:50)
Decision Trees, Random Forests & Gradient Boosting (XGBoost)
(08:57)
Unsupervised Learning: K-Means Clustering & Dimensionality Reduction (PCA)
(20:36)
Deep Learning & Production Model Serving
Introduction to Neural Networks & PyTorch Tensors
(11:30)
Hyperparameter Tuning, Cross-Validation & Model Serialization
(09:30)
Packaging Models into FastAPI Microservices for Production
(16:45)
Lecture
Decision Trees, Random Forests & Gradient Boosting (XGBoost)
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