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Intermediate6 tutorials

Level Up Your Skills

Build on your foundations with deep learning, NLP, and advanced techniques. Hands-on projects to solidify your understanding.

Prerequisites

  • Python programming fundamentals
  • Basic understanding of linear algebra
  • Completed beginner tutorials or equivalent
  • Familiarity with NumPy and Pandas
Review Beginner Tutorials

Image Classification with CNNs

Build a convolutional neural network to classify images. Understand convolutions, pooling, and feature maps.

Convolution LayersPoolingFeature Maps+4 more
45 min7 lessons

Natural Language Processing Basics

Process and analyze text data using modern NLP techniques. Tokenization, embeddings, and sentiment analysis.

TokenizationWord EmbeddingsTF-IDF+5 more
60 min8 lessons

Time Series Forecasting

Predict future values using LSTM networks and traditional statistical methods like ARIMA.

ARIMA ModelsLSTM NetworksSeasonality+3 more
50 min6 lessons

Ensemble Methods Deep Dive

Master Random Forests, Gradient Boosting, and XGBoost for improved model performance.

Random ForestGradient BoostingXGBoost+4 more
55 min7 lessons

Feature Engineering Masterclass

Transform raw data into powerful features. Learn encoding, scaling, and creating derived features.

One-Hot EncodingFeature ScalingPolynomial Features+2 more
40 min5 lessons

Model Evaluation & Metrics

Go beyond accuracy. Learn precision, recall, F1, ROC curves, and when to use each metric.

Confusion MatrixPrecision & RecallF1 Score+2 more
35 min5 lessons

Ready for Advanced Topics?

Master transformers, recommendation systems, and production deployment.

Continue to Advanced
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