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          • Lesson 1
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          • Lesson 1 - Image Recognition
          • Lesson 2 - Computer Vision: Deeper Applications
          • Lesson 3 - Multi-label, Segmentation, Image Regression, and More
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          • Lesson 8 - Artistic Style
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          • Lesson 14 - Time Series & Segmentation
        • Deep Learning Part 2: 2018 Edition (v2)
          • Lesson 8 - Object Detection
          • Lesson 9 - Single Shot Multibox Detector (SSD)
          • Lesson 10 - Transfer Learning for NLP and NLP Classification
          • Lesson 11 - Neural Translation; Multi-modal Learning
          • Lesson 12 - DarkNet; Generative Adversarial Networks (GANs)
          • Lesson 13 - Image Enhancement; Style Transfer; Data Ethics
          • Lesson 14 - Super Resolution; Image Segmentation with U-Net
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        • Machine Learning: 2017 Edition
          • Lesson 1 - Introduction to Random Forests
          • Lesson 2 - Random Forest Deep Dive
          • Lesson 3 - Feature Engineering
          • Lesson 4 - Random Forest Interpretation
          • Lesson 5 - Train vs Test
          • Lesson 6 - What is Machine Learning and Why Do We Use It
          • Lesson 7 - Decision Trees Ensemble
          • Lesson 8 - Basic Neural Networks
          • Lesson 9 - SGD; Neural Network Training; Broadcasting
          • Lesson 10 - Logistic Regression; NLP; Naive Bayes
          • Lesson 11 - Structured and Time-Series Data
          • Lesson 12 - Entity Embeddings; Data Science and Ethics
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Deep Learning Part 1: Practical Deep Learning for Coders

Previousfast.aiNextDeep Learning Part 1: 2018 Edition (v2)

Last updated 6 years ago

Deep Learning Part 1: 2018 Edition (v2)
Deep Learning Part 1: 2019 Edition (v3)