Applied AI from Scratch Training Course
This is a 4 day course introducing AI and it's application. There is an option to have an additional day to undertake an AI project on completion of this course.
Course Outline
Supervised learning: classification and regression
- Bias-variance trade off
- Logistic regression as a classifier
- Measuring classifier performance
- Support vector machines
- Neural networks
- Random forests
Unsupervised learning: clustering, anomaly detetction
- 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 cell
Practical examples of problems that AI can solve, e.g.
- image analysis
- forecasting complex financial series, such as stock prices,
- complex pattern recognition
- natural language processing
- recommender systems
Software platforms used for AI applications:
- TensorFlow, Theano, Caffe and Keras
- AI at scale with Apache Spark: Mlib
Understand limitations of AI methods: modes of failure, costs and common difficulties
- overfitting
- biases in observational data
- missing data
- neural network poisoning
Requirements
There are no specific requirements needed to attend this course.
Open Training Courses require 5+ participants.
Applied AI from Scratch Training Course - Booking
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Applied AI from Scratch - Consultancy Enquiry
Consultancy Enquiry
Testimonials (3)
The trainer explained the content well and was engaging throughout. He stopped to ask questions and let us come to our own solutions in some practical sessions. He also tailored the course well for our needs.
Robert Baker
Course - Deep Learning with TensorFlow 2.0
Tomasz really know the information well and the course was well paced.
Raju Krishnamurthy - Google
Course - TensorFlow Extended (TFX)
Very updated approach or CPI (tensor flow, era, learn) to do machine learning.
Paul Lee
Course - TensorFlow for Image Recognition
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