Machine Learning

As data and AI become the engine of business change, we need to learn the lessons of the past to avoid expensive failures.

This is a summary of the sessions I attended at SQLbits 2024 - Europe's largest expert led data conference. This year SQLBits was hosted at Farnborough IECC, Hampshire.

This is a summary of the sessions I attended at SQLbits 2023 in Newport Wales, which is Europe's largest expert led data conference.

Some of my thoughts inspired whilst helping out on the farm over the weekend. What is the future of work given the increasing presence of machines in our day to day lives? In which situations can AI deliver greatest value? How can we ease the stress of digital transformation on people who are impacted by it?

Summary of key themes from the Doing Data Together conference hosted virtually by The Scotsman newspaper and Edinburgh University in November 2020. The conference agenda was pivoted to focus on the use of data to help tackle the Covid-19 pandemic. It provided a fascinating insight into the lessons learned.

Jess and Carmel recently gave a talk at Azure Oxford on Combatting illegal fishing with Machine Learning and Azure - for less than £10 / month. The recording of that talk is now available for viewing!The talk focuses on the recent work we completed with OceanMind. They run through how to construct a cloud-first architecture based on serverless and data analytics technologies and explore the important principles and challenges in designing this kind of solution. Finally, we see how the architecture we designed through this process not only provides all the benefits of the cloud (reliability, scalability, security), but because of the pay-as-you-go compute model, has a compute cost that we could barely believe!

Wardley Maps are a fantastic tool to help provide situational awareness, in order to help you make better decisions. We use Wardley Maps to help our customers think about the various benefits and trade-offs that can be made when migrating to the Cloud. In this blog post, Jess Panni demonstrates how we used Wardley Maps to plan the migration of OceanMind to Microsoft Azure, and how the maps highlighted where the core value of their platform was, and how PaaS and Serverless services offered the most value for money for the organisation.

Ed attended NDC London 2020, along with many of his endjin colleagues. In this post he summarises and reflects upon his favourite sessions of the conference including; "OWASP Top Ten proactive controls" by Jim Manico, "There's an Impostor in this room!" by Angharad Edwards, "How to code music?" by Laura Silvanavičiūtė, "ML and the IoT: Living on the Edge" by Brandon Satrom, "Common API Security Pitfalls" by Philippe De Ryck, and "Combatting illegal fishing with Machine Learning and Azure - for less than £10 / month" by Jess Panni & Carmel Eve.

Endjin attended Microsoft's AI for Good hackathon at the IET in London, highlighting the potential of tech to amplify good deeds.

In January 2020, Carmel is speaking about creating high performance geospatial algorithms in C# which can detect suspicious vessel activity, which is used to help alert law enforcement to illegal fishing. The input data is fed from Azure Data Lake Storage Gen 2, and converted into data projections optimised for high-performance computation. This code is then hosted in Azure Functions for cheap, consumption based processing.

Machine learning often seems like a black box. This post walks through what's actually happening under the covers, in an attempt to de-mystify the process!Neural networks are built up of neurons. In a shallow neural network we have an input layer, a "hidden" layer of neurons, and an output layer. For deep learning, there is simply more hidden layers which allows for combining neuron's inputs and outputs to build up a more detailed picture.If you have an interest in Machine Learning and what is really happening, definitely give this a read (WARNING: Some algebra ahead...)!

Explore data analysis & ETL with Databricks Notebooks on Azure. Utilize Spark's unified analytics engine for big data & ML, and integrate with ADF pipelines.

There is a lot of hype around AI & ML. Here's an example of using ML.NET & Azure Functions to deliver a series of micro-optimisations, to automate a series of 1 second tasks. When applied to business processes, this is what the 4th Industrial Revolution could look like.

When he joined endjin, Technical Fellow Ian sat down with founder Howard for a Q&A session. This was originally published on LinkedIn in 5 parts, but is republished here, in full. Ian talks about his path into computing, some highlights of his career, the evolution of the .NET ecosystem, AI, and the software engineering life.

Learn to use SQL Server's Python integration for efficient data handling. Eliminate clunky transfers and easily operationalize Python models/scripts.

Learn what types of things an apprentice gets up to at endjin a few months after joining. You could be learning about Neural Networks: algorithms which mimic the way biological systems process information. You could be attending Microsoft's Future Decoded conference, learning about Bots, CosmosDB, IoT and much more. Hopefully, you wouldn't be in hospital after a ruptured appendix!

Structured apprenticeships provide a great way to build skills whilst getting real-life experience. Endjin's apprenticeship scheme has been refined over years, with an optimal mixture of training, project work, and exposure to commercial processes - a scheme which is designed to build strong foundations for a well-rounded Software Engineering consultant. This post explains the transition from university to an apprenticeship at endjin, including the types of work an apprentice could end up doing, and some examples of real-life learnings from a real-life apprentice.

We ran a two day hackathon with Watchfinder and Microsoft to build a conversational experience to automate the 'sell your watch experience'.

A career in software engineering doesn't need to start with a Computer Science degree. The underlying traits of problem solving, a willingness to learn and the ability to collaborate well can be built in any field. Internships provide a great way to get your foot-in-the-door in the professional world, and arm you with some real-life experience for future endeavours. This post describes an internship at endjin, including the type of work you could be asked to do and what you could learn.

Explore creating and testing an Azure ML Studio web service using Postman for efficient machine learning model production.

What do machine learning and data science actually mean? This post digs into the detail behind the endjin approach to structured experimentation, arguing that the "science" is really all about following the process, allowing you to iterate to insights quickly when there are no guarantees of success.

We have produced an insightful booklet called "Embracing Disruption - Financial Services and the Microsoft Cloud" which examines the challenges and opportunities for the Financial Service Industry in the UK, through the lens of Microsoft Azure, Security, Privacy & Data Sovereignty, Data Ingestion, Transformation & Enrichment, Big Compute, Big Data, Insights & Visualisation, Infrastructure, Ops & Support, and the API Economy.

This post looks at what machine learning really is (and isn't), dispelling some of the myths and hype that have emerged as the interest in data science, predictive analytics and machine learning has grown. Without any hard guarantees of success, it argues that machine learning as a discipline is simply trial and error at scale – proving or disproving statistical scenarios through structured experimentation.

Azure Machine Learning’s SMOTE module helps balance imbalanced training data by generating synthetic samples, improving model accuracy for multi-class classification.