jgadelugo / holbertonschool-machine_learning

Holberton School Machine Learning

Description

Holberton School Machine Learning Specialization. For more information click Here.

Mathematics:

• Intro to Linear Algebra
• Intro to Calculus
• Intro to Plotting
• Intro to Probability
• Advanced Linear Algebra
• Advanced Probability

Supervised Learning:

• Binary Classification
• Multiclass Classification
• Optimization Techniques
• Regularization Techniques
• Convolutional Neural Networks
• Deep Convolutional Architectures
• Recurrent Neural Networks
• Transformers
• Seq-to-Seq modeling
• Object Detection
• Face Verification
• Neural Style Transfer
• Stock predictions
• Speech to Text
• Machine Translation
• Recommender Systems

Unsupervised Learning:

• Dimensionality Reduction
• Clustering
• Embeddings
• Autoencoders
• Generative Adversarial Networks
• Hyperparameter Optimization
• Hidden Markov Models

Reinforcement Learning:

• Agent-Environment Framework
• Multi-armed Bandit problems
• Markov decision process
• Exploration vs Exploitation
• Policy and Value Functions
• Temporal Difference Learning
• Deep Reinforcement Learning
• Develop a Game Agent

The Pipeline:

• Web scraping
• Labeling data
• SQL & NoSQL databases
• Map Reduce
• Hosting on cloud platforms

Authors

• Jose Alvarez de Lugo [e-mail] Linked IN