Classical ML/DL Practitioner Curriculum

Subject: Classical ML/DL Practitioner Curriculum

17 chapters

Chapters

  1. 1 Supervised Learning
    symphonic afro-cuban jazz, arabic acid house · 5:37
    Dive into the foundational world of supervised learning, where linear regression, Ridge, Lasso, and Elastic Net regularization techniques come to life through rhythm and melody, giving you an intuitive grasp of how models learn from labeled data and control complexity.
  2. 2 Unsupervised Learning
    piano acid techno, acoustic blues mariachi, breakbeat balkan brass band · 4:57
    Explore the fundamentals of unsupervised learning, where algorithms uncover hidden structure and patterns in unlabeled data without human guidance, including how clustering techniques like K-means work to group similar data points together.
  3. 3 Model Selection & Evaluation
    symphonic afro-cuban jazz, arabic acid house · 4:51
    Dive into the critical balance between bias and variance that determines whether your model generalizes or crumbles on unseen data, mastering the fundamental principles of model selection and evaluation that separate reliable ML systems from ones that only perform well in training.
  4. 4 Feature Engineering (The Craft)
    new jack swing big band, dreamy boom bap, bubblegum dance chanson · 3:31
    Dive into the art of transforming raw, messy data into meaningful signals through powerful techniques like target encoding, frequency mapping, and feature hashing. You'll learn how to craft smarter inputs that help machine learning models cut through the noise and find what truly matters.
  5. 1 Foundations
    piano acid techno, acoustic blues mariachi, breakbeat balkan brass band · 4:30
    A deep dive into the foundational architecture of neural networks, exploring how layers stack and data flows forward, culminating in the powerful universal approximation theorem that defines what these systems can ultimately learn to represent.
  6. 2 Convolutional Neural Networks
    new jack swing big band, dreamy boom bap, bubblegum dance chanson · 4:15
    Dive into the architecture and mechanics of Convolutional Neural Networks, tracing their origins from LeCun's groundbreaking LeNet-5 to the core building blocks—filters, strides, padding, and dilation—that make image recognition possible.
  7. 3 Sequence Models
    new jack swing big band, dreamy boom bap, bubblegum dance chanson · 4:23
    Dive into the evolution of sequence models, tracing the journey from vanilla RNNs and their notorious vanishing gradient problem to the architectures designed to overcome them.
  8. 4 Practical Deep Learning
    symphonic afro-cuban jazz, arabic acid house · 4:44
    A deep dive into the hands-on craft of training neural networks, covering essential techniques like learning rate scheduling, cosine annealing, mixed precision training, and debugging strategies that turn chaotic training runs into stable, high-performing models.
  9. 1 Ranking & Recommendations
    symphonic afro-cuban jazz, arabic acid house · 4:39
    Dive into the world of recommendation systems, where collaborative filtering and matrix factorization reveal how platforms learn your preferences and serve up eerily accurate suggestions. You'll grasp how algorithms like Alternating Least Squares (ALS) analyze user-item behavior patterns to predict what you'll love before you even know it.
  10. 2 Fraud Detection & Anomaly Detection
    new jack swing big band, dreamy boom bap, bubblegum dance chanson · 4:09
    Dive into the challenge of fraud and anomaly detection, where imbalanced datasets make traditional classification methods fall short, and discover the specialized techniques needed to catch rare but critical outliers hiding among overwhelming amounts of clean data.
  11. 3 Time Series & Forecasting
    piano acid techno, acoustic blues mariachi, breakbeat balkan brass band · 4:26
    Dive into the world of time series analysis and forecasting, where ARIMA models, exponential smoothing, and autoregressive techniques reveal hidden patterns in sequential data to predict future trends with precision.
  12. 4 Search & Information Retrieval
    french psybient, harpischord symphonic metal, piano afroswing · 5:01
    Dive into the foundations of search and information retrieval, exploring how classic algorithms like TF-IDF and BM25 rank and surface relevant documents from massive collections. You'll gain a clear understanding of inverted indices, term weighting, and length normalization — the mathematical machinery powering modern search engines.
  13. 5 Other High-Value Niches
    french psybient, harpischord symphonic metal, piano afroswing · 4:18
    Dive into five lucrative machine learning niches beyond the obvious, exploring how concepts like price elasticity, gradient descent, and A/B testing unlock real-world value across industries. You'll discover how to identify and position yourself in high-demand domains where classical ML and deep learning skills command serious market attention.
  14. 1 Data Pipeline Work
    french psybient, harpischord symphonic metal, piano afroswing · 5:27
    Dive into the foundational world of data pipelines, exploring how raw, messy data gets extracted, transformed, and loaded through ETL and ELT patterns to power real-world machine learning systems.
  15. 2 Model Serving & Deployment
    symphonic afro-cuban jazz, arabic acid house · 4:16
    Diving into the critical decision point between batch and real-time inference, 2 Model Serving & Deployment breaks down how to choose the right serving strategy and understand the fundamental tradeoffs between latency and throughput when taking a trained model to production.
  16. 3 MLOps & Monitoring
    piano acid techno, acoustic blues mariachi, breakbeat balkan brass band · 4:36
    Dive into the world of MLOps as this chapter breaks down the essential tools and practices for tracking experiments, logging metrics, and monitoring model performance. You'll learn how platforms like MLflow and Weights & Biases bring order to the chaos of hyperparameter tuning and training workflows.
  17. 4 Tools & Ecosystem
    piano acid techno, acoustic blues mariachi, breakbeat balkan brass band · 4:25
    Dive into the essential toolkit every machine learning practitioner needs, exploring how Python, NumPy, Pandas, Scikit-learn, PyTorch, and SQL work together to power real-world ML workflows from raw data to predictions.