What we're about

Learning Machine Learning doesn't have to be hard! We are here to make AI education accessible to everyone. AI is not just the future - it's now.
Beginner's Machine Learning (BML) is a meetup group dedicated to learning machine learning, computer vision, natural language processing, knowledge representation, and artificial intelligence via hands-on workshops. We run workshops for all skill levels who want to join this exciting field and our meetings cover research papers and new algorithms in the field. We also organise fun and engaging meetups, hackathons and networking events related to AI and ML.
Join our Slack Channel to collaborate, discuss ideas and post questions!

Slack Channel:
Click here to Join

YouTube Channel:
Click here to watch our past workshops

A list of our upcoming events in 2022:
[R] Recording is now available on our YouTube Channel.

  1. Introduction To Neural Networks using Tensorflow [R]
  2. Train and Deploy AI models on the cloud using Tensorflow [R]
  3. Convolutional Neural Networks - Part 1 - Image Classification [R]
  4. Convolutional Neural Networks - Part 2 - Object Detection
  5. Convolutional Neural Networks - Part 3 - Semantic Segmentation
  6. Convolutional Neural Networks - Part 4 - Style Transfer
  7. Computer Vision - Processing your own images and videos
  8. Cloud Computing Fundamentals – Learn how to develop solutions on Microsoft Azure
  9. Data Streaming on the cloud - Analyse live-stream data with machine learning on Azure
  10. Clustering – Clustering geospatial data with unsupervised machine learning on AWS
  11. Transfer Learning on Cloud - Classify colour images with CNNs and Tensorflow Keras on Google Cloud
  12. Natural Language Processing - Beginner’s Guide to NLP programming with Tensorflow
  13. Time-Series Data Analysis - Time-series Forecasting with Sci-kit Learn ML Library
  14. Big Data Engineering - BIG data engineering with Azure Databricks and Apache Spark

List of recommended books by BML:
1. Python for Data Analysis by Wes McKinney
2. Data Science from Scratch by Joel Grus
3. The Hundred-Page Machine Learning Book by Andriy Burkov 
4. Deep Learning with Python by Francois Chollet
5. Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurelien Geron
6. Python Machine Learning by Sebastian Raschka
7. Grokking Deep Learning by Andrew W Trask

Beginners Machine Learning Code of Conduct
Beginners Machine Learning is dedicated to enabling its members to use machine learning and data science technologies for advancing their careers. This includes organising and delivering events where we seek to provide a respectful, friendly, professional experience for everyone, regardless of gender, sexual orientation, physical appearance, disability, age, race or religion. We do not tolerate any behaviour that is harassing or degrading to any individual, in any form. Individuals are responsible for knowing and abiding by these standards. We encourage everyone to assist in creating a welcoming and safe environment.
Please report any concerns, suspicious or disruptive activity or behaviour to the group leadership team.
Beginners Machine Learning reserves the right to refuse admittance to or remove any person from any of its events at any time at its discretion.

Upcoming events (1)

Beginner's Guide to Semantic Segmentation With Convolutional Neural Networks

Learn how to build Semantic Segmentation models in Tensorflow using Convolutional Neural Networks (CNNs).

Tensorflow is the core open-source library to help you develop and train ML models. Yet it can remain a mystery how it can be used with your own image datasets. Join this workshop to learn how to use it.

In this Beginners Machine Learning workshop, you will learn about:

  • What is Semantic Segmentation?
  • A review of the most popular Semantic Segmentation methods in literature: Encoder-Decoders, U-Nets, Full CNNs, Pyramid Scene Parsing Network (PSPNet), DeepLab, ParseNet, etc.
  • How to build a semantic segmentation model from scratch on Google Colab and train it on a GPU
  • How to run semantic segmentation models on images and videos

In this training, we will approach the problem from the ground up: Reviewing how semantic segmentation models work without getting bogged down in the detail and getting some models training as fast as possible. The workshop materials will be delivered in a combination of coding exercises and lectures.

This is A FREE training not to be missed.

Please note training notebooks and materials will be released after the session only to the attendees free of charge.

In the coming sessions, we will explore more advanced concepts such as data preparation and analysis.


The event is free and everybody is welcome to register. Please register below to register your attendance.


Questions you will answer in this workshop:

  • What are the most popular semantic segmentation models? How do they work?
  • How can I prepare my own image datasets for deep learning?
  • How to architect my own semantic segmentation models?
  • How to use transfer learning with CNNs?


6:00 PM - 8:00 PM Monday 23th May 2022


Ali Parandeh, CEng
Chartered Software Engineer
Microsoft Certified Azure Data Scientist & Developer


  1. What will I need to bring to this workshop?
    Just a pen, paper and a laptop.
  2. I am an absolute beginner. Can I still come?
    This is an intermediate-level workshop. We expect you to have intermediate knowledge of Python (Lists, Dictionaries, Loops, Functions, classes)
    Knowledge of data science libraries (NumPy, matplotlib, pandas, scikit-learn) will be advantageous.
  3. Do I need to pay money for this workshop or Microsoft Azure?
    No. This workshop is a free online workshop.

Recommended Reading:



The event is free and everybody is welcome to register. Please register below.



Photos (77)