1st lesson free
The profile of Adrian and their contact details have been verified by our experts
Adrian
- Rate €103
- Response 7h
-
Students3
Number of students Adrian has accompanied since arriving at Superprof
Number of students Adrian has accompanied since arriving at Superprof
€103/h
Contact
1st lesson free
- Machine learning
Machine learning and data science with explanations and codes for beginners up to computer science or statistics undergraduate and graduate students
- Machine learning
Lesson location
About Adrian
I have been teaching in top universities for over 20 years and am a senior professor. I have taught and/or authored papers on these topics. You will receive dedicated teaching, full explanations and help instructions on how to implement the methods you learn. Let me know your level and the lessons can be designed accordingly, either for pure beginners or more advanced learners.
See more
About the lesson
- Primary
- Junior Cycle
- Transition Year
- +12
levels :
Primary
Junior Cycle
Transition Year
Fifth Year
Sixth Year
Adult education
Bachelor's degree
Master's degree
Diploma
Doctorate degree
Beginner
Intermediate
Advanced
Professional
Kids
- English
All languages in which the lesson is available :
English
Do you want to understand machine learning either as a beginner or an intermediate/advanced student? These lessons can start at the appropriate level, depending on your existing knowledge. Included for free will be codes in Python and instructions on how to run and adapt them. Topics that can be covered include (but are not limited to) - Background in linear algebra, vector calculus, probability, random variables/vectors and random processes - Background in convex optimisation, optimisation for machine learning, stochastic gradient descent (momentum, AdaGrad, Nesterov Accelerated Gradient, RMSProp and Adam) - Linear regression, regularisation (ridge, lasso, Elastic Net; training via proximal gradient methods and coordinate descent); maximum likelihood approaches; basis function methods; multi-output regression; bias-variance decomposition; methods to prevent overfitting; measures of error; cross validation, grid searches and nested cross validation; information criteria and Kullback-Liebler divergence for model selection; nonlinear least squares; Bayesian linear regression; maximum a-posterior estimates; connections to regularisation; evidence approximation and Laplace approximation - First look at non-parametric regression approaches; including local linear and polynomial regression and scatterplot smoothing; k-nearest neighbour regression; decision tree regression and cost complexity pruning; additive and generalised additive models - Linear classification:linear discriminant approaches; probabilistic generative models including naive Bayes classifier; maximum likelihood in classification models; Fisher's discriminant analysis; logistic regression; least-squares classification; error measures; generalised linear models; multi-class problems - Kernel methods and sparse kernel machines for regression: dual representations and kernel ridge regression; the Nadaraya-Watson model; support vector and relevance vector regression; Gaussian process models, including point estimates, mean-field variational inference and Markov Chain Monte Carlo sampling. Also covered are multi-output Gaussian process models, including coregionalisation models and low-rank approximations - An introduction to neural networks (multi-layer perceptrons MLPs) ; deep learning with MLPs, convolutional networks (CNNs); recurrent networks (RNNs); graph networks (GNNs); encoder-decoder models; auto-encoders; training stochastic gradient descent and backpropagation - Nonlinear classification: neural network classifiers, maximal margin classifiers and kernel support vector machines, relevance vector classification; decision tree classifiers; kNN classifiers; Gaussian process classification - Unsupervised learning: dimension reduction, clustering, density estimation: - principal component analysis, multi-dimensional scaling and independent component analysis; Isomap, diffusion maps, kernel PCA and local linear embedding; - clustering using k-means and k-mediod, hierarchical clustering, spectral clustering and Gaussian mixture models with expectation-maximization - density estimation using histograms, kernel density estimation, Gaussian mixture models, the Parzen window method and mixtures of experts - Advanced topics: ensemble methods: bagging (bootstrap aggregating) and boosting, including gradient boosting machines/random forests; - Time series and sequence data using embeddings, supervised machine learning, autoregression via linear/nonlinear state-space models and RNNs
See more
Review
All of our reviews are collected by us and are 100% reliable. They correspond to a real experience had by the students of Adrian.
1 review
Deadly! Very knowledgeable tutor, friendly and engaging. Great learning experience
- Very able fast learner, pleasure to teachAdrian's response :
View more reviews
See more
Rates
Rate
- €103
Pack prices
- 5h: €517
- 10h: €1033
online
- €103/h
free lessons
The first free lesson with Adrian will allow you to get to know each other and clearly specify your needs for your next lessons.
- 1hr
Similar Machine learning tutors in London
Aaqid
Dublin 8 & Online
- €16/h
- 1st lesson free
ANKIT
Maynooth & Online
- €30/h
- 1st lesson free
Eduardo
Dublin & Online
- €50/h
Dr Abdur Rahman
Dublin & Online
- €30/h
Zahid
Ennis & Online
- €35/h
- 1st lesson free
Lucas
Dublin & Online
- €23/h
- 1st lesson free
Pritish
& Online
- €30/h
Saurabh
Dublin & Online
- €10/h
Chris
Dublin & Online
- €40/h
- 1st lesson free
Robbie
Galway & Online
- €50/h
- 1st lesson free
Emils
Dublin 8 & Online
- €15/h
- 1st lesson free
Neri
Dublin 16 & Online
- €25/h
Sagar
Dublin & Online
- €60/h
- 1st lesson free
Haritha
Dublin & Online
- €5/h
- 1st lesson free
Mohan
Limerick & Online
- €20/h
- 1st lesson free
Aparna
Dublin & Online
- €18/h
- 1st lesson free
Sanat
Dublin & Online
- €30/h
- 1st lesson free
Maria
Carlow & Online
- €30/h
- 1st lesson free
Théo
Dublin
- €30/h
Adrien
Dublin & Online
- €50/h
- 1st lesson free
-
See Machine learning tutors
