WEEK 2
Welcome to the course! This week, please go through Modules 0 and Modules 1.
A live interactive session will be held on Thursday at 9am, where the instructors will be available to answer any questions.
There will be NO lab session this week. You may, however, want to consider picking up Python and Numpy to prepare yourself for the coursework assignments.
You should also start forming groups of 4 people for your coursework.
WEEK 3
Welcome to Week 3. For this week, please go through Module 2 where we will discuss two algorithms: K-nearest neighbours and decision trees.
The coursework has also been released. Please download the specifications and dataset from CATE.
There will be a lab session this week on Wednesday 9am-11am BST on Microsoft Teams. Our Tutorial Helpers will be there to support you with any questions or problems with the coursework that you may have.
A live interactive session will be held on Thursday 9am-10am BST, where Antoine will answer any questions you may have about this week's topic.
If you need help with Python or Numpy, you can make use of the study materials from Josiah's Python Programming module. There is specifically an introductory guide to NumPy. Alternatively, try the official NumPy tutorials.
WEEK 4
Welcome back! This week is all about evaluating machine learning systems.
Please go through Module 3 where Marek will discuss various topics related to machine learning evaluation.
As usual, there will be a lab session this week on Wednesday 9am-11am GMT on Microsoft Teams. This is where you can get help from our Tutorial Helpers with any questions or issues you may have with your coursework. The CELCAT link should bring you to the correct Microsoft Teams this time (sorry for the confusion last week!)
The live interactive session will also be held as usual on Thursday 9am-10am GMT, where Marek will be there to answer your questions on evaluating machine learning systems.
WEEK 5
Welcome to Week 5! This week, you will start exploring the current hottest craze in ML: neural networks.
Please go through Module 4. Marek will first introduce you to a basic model called linear regression, before showing you how it relates to neural networks.
The lab session is on as usual on Wednesday 9am-11am GMT on Microsoft Teams. This is your chance to get some last minute help for your coursework from the Tutorial Helpers.
The coursework is due on Friday 7pm GMT.
The live interactive session is on Thursday 9am-10am GMT as usual, where Marek will answer all your pressing Neural Network questions.
WEEK 6
We are now in Week 6! This week, you will continue exploring more neural network goodness. Brace yourselves - the discussions will start to become more exciting (and advanced) from this week onwards!
Please go through Module 5. Marek will pick up from where he stopped last week, and continue his exciting discussions on neural networks.
The second coursework has also been released. Please download the specifications from CATE or Materials. This coursework 2 will be done in the same groups as coursework 1. You should have received a link to your group Gitlab repo for the coursework via email. This can also be accessed via LabTS. Your group will work collaboratively on this Gitlab repo. For this coursework you will have to submit a report and also a SHA1 token to your Gitlab commit that you intend to submit. The SHA1 token can be submitted to CATE via the LabTS interface.
As usual, the lab session is on Wednesday 9am-11am GMT on Microsoft Teams, where you can seek help on the new coursework from our dedicated team of Tutorial Helpers.
Also as usual is the live interactive session on Thursday 9am-10am GMT, where Marek will answer more of your Neural Network questions.
WEEK 7
Welcome to Week 7. I guess that by this time you have had enough of supervised learning and neural networks. As a change of pace, this week we will look at the other main machine learning setting called unsupervised learning, where the training labels are not provided.
Please go through Module 6. Antoine is back, this time to talk about the fascinating world of unsupervised learning.
As with every week, the lab session is still happening on Wednesday 9am-11am GMT. Our team of Tutorial Helpers will be available to help you with your questions regarding the second coursework.
Antoine will also answer your questions on unsupervised learning in the usual live interactive session on Thursday 9am-10am GMT.
WEEK 8
Welcome to Week 8, which is officially our final week of lectures! This week, we will look at our final topic: evolutionary algorithms. This topic is very different from everything you have seen so far, although the key underlying ML idea is still the same, i.e. optimising some objective!
Please go through Module 7, where Antoine will introduce you to evolutionary algorithms.
The second coursework is due on Friday 7pm GMT.
Our final lab session is happening as usual on Wednesday 9am-11am GMT. Please use this opportunity to get some last minute help for the second coursework from our dedicated team of Tutorial Helpers.
The usual live interactive session is on Thursday 9am-10am GMT, where Antoine will answer any questions you might have on evolutionary algorithms.
WEEK 9
Welcome to Week 9 - you have survived your courseworks! Great work, and all the best with your revisions!
The only thing happening this week for Introduction to Machine Learning is our live revision/Q&A session on Wednesday 9am-11am GMT. Please post your questions by Tuesday 5pm via our Mentimeter link for a better chance of it being answered.
We hope you enjoyed the course, and we look forward to seeing you apply Machine Learning in the future to do great things!
Update 1: The recording of the live revision/Q&A session is available here:
Update 2: We have prepared a final "grand quiz" to further test your understanding of all the topics that we have covered: