DeepLearning.AI - Advanced Learning Algorithms
5.0 /5- Offered byCoursera
Advanced Learning Algorithms at Coursera Overview
Duration | 30 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Advanced Learning Algorithms at Coursera Highlights
- Earn a Certificate upon completion
Advanced Learning Algorithms at Coursera Course details
- The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online
- In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications
- This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field
- It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.)
- By the end of this Specialization, you will have mastered key theoretical concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems
Advanced Learning Algorithms at Coursera Curriculum
Neural Networks
Welcome!
Neurons and the brain
Demand Prediction
Example: Recognizing Images
Neural network layer
More complex neural networks
Inference: making predictions (forward propagation)
Inference in Code
Data in TensorFlow
Building a neural network
Forward prop in a single layer
General implementation of forward propagation
Is there a path to AGI?
How neural networks are implemented efficiently
Matrix multiplication
Matrix multiplication rules
Matrix multiplication code
Practice quiz: Neural networks intuition
Practice quiz: Neural network model
Practice quiz: TensorFlow implementation
Practice quiz: Neural network implementation in Python
Neural network training
TensorFlow implementation
Training Details
Alternatives to the sigmoid activation
Choosing activation functions
Why do we need activation functions?
Multiclass
Softmax
Neural Network with Softmax output
Improved implementation of softmax
Classification with multiple outputs (Optional)
Advanced Optimization
Additional Layer Types
Practice quiz: Neural Network Training
Practice quiz: Activation Functions
Practice quiz: Multiclass Classification
Practice quiz: Additional Neural Network Concepts
Advice for applying machine learning
Deciding what to try next
Evaluating a model
Model selection and training/cross validation/test sets
Diagnosing bias and variance
Regularization and bias/variance
Establishing a baseline level of performance
Learning curves
Deciding what to try next revisited
Bias/variance and neural networks
Iterative loop of ML development
Error analysis
Adding data
Transfer learning: using data from a different task
Full cycle of a machine learning project
Fairness, bias, and ethics
Error metrics for skewed datasets
Trading off precision and recall
Practice quiz: Advice for applying machine learning
Practice quiz: Bias and variance
Practice quiz: Machine learning development process
Decision trees
Decision tree model
Learning Process
Measuring purity
Choosing a split: Information Gain
Putting it together
Using one-hot encoding of categorical features
Continuous valued features
Regression Trees (optional)
Using multiple decision trees
Sampling with replacement
Random forest algorithm
XGBoost
When to use decision trees
Acknowledgements
Practice quiz: Decision trees
Practice quiz: Decision tree learning
Practice quiz: Tree ensembles
Advanced Learning Algorithms at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Advanced Learning Algorithms at Coursera Students Ratings & Reviews
2 Ratings- 4-52
Student Forum
Anything you would want to ask experts?