Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Supervised Learning: Classification and Regression
- Understanding the bias-variance trade-off
- Logistic regression as a classification tool
- Evaluating classifier performance
- Support vector machines
- Neural networks
- Random forests
Unsupervised Learning: Clustering and Anomaly Detection
- Principal component analysis
- Autoencoders
Advanced Neural Network Architectures
- Convolutional neural networks for image analysis
- Recurrent neural networks for time-structured data
- The long short-term memory (LSTM) cell
Practical Applications: Solving Real-World Problems
- Image analysis
- Forecasting complex financial series, such as stock prices
- Complex pattern recognition
- Natural language processing
- Recommender systems
Software Platforms for AI Applications
- TensorFlow, Theano, Caffe, and Keras
- AI at scale using Apache Spark MLlib
Understanding Limitations of AI Methods: Failure Modes, Costs, and Common Challenges
- Overfitting
- Biases in observational data
- Missing data issues
- Neural network poisoning
Requirements
This course has no specific prerequisites; it is open to all interested attendees.
28 Hours
Testimonials (2)
The training was organized and well-planned out, and I come out of it with systematized knowledge and a good look at topics we looked at
Magdalena - Samsung Electronics Polska Sp. z o.o.
Course - Deep Learning with TensorFlow 2
I really liked the end where we took the time to play around with CHAT GPT. The room was not set up the best for this- instead of one large table a couple of small ones so we could get into small groups and brainstorm would have helped
