Machine Learning
Transform your business with cutting-edge machine learning solutions from &Element. Our dedicated team of machine learning developers use complex algorithms and data-driven insights to innovate and solve challenges across industries. Elevate your operations, customer service, and product offerings with precision and efficiency.
We’ve helped hundreds of businesses digitally optimise their company and increase profits.
230% average increase in ROI across our suite of services.
235+ projects completed since we were founded in 2015.
45m people reached across the world through work.
What is machine learning?
Machine learning is a subset of artificial intelligence (AI) that allows systems to learn from experience and improve automatically without being explicitly programmed. This field focuses on developing computer programs that can access data and use it to learn for themselves.
The learning process begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples we provide. The primary aim is to allow the computers to learn automatically without human intervention or assistance and adjust actions accordingly.
What does a machine learning developer do?
A machine learning developer specialises in creating algorithms and statistical models computers use to perform specific tasks without explicit instructions. This role is critical in numerous fields, such as finance for credit scoring, healthcare for predictive diagnostics, marketing for customer insights, and more, where making data-driven decisions is crucial for success.
A machine learning developer works with a variety of programming languages like Python, R, and Scala, and they utilise libraries such as TensorFlow, PyTorch, and Scikit-learn to build models that can analyse complex data sets to predict outcomes and automate decision-making processes.
How can machine learning benefit your business?
Hiring a machine learning developer can significantly benefit your business by optimising and automating decision-making processes, enhancing predictive accuracy, and driving innovation. For example, in the financial sector, machine learning models can assess credit risk more accurately than traditional methods.
In marketing, these models can analyse consumer data to tailor marketing strategies that significantly boost conversion rates. Moreover, machine learning can streamline supply chain logistics by predicting demand spikes, ensuring better stock management. All this potential makes a machine learning developer a valuable asset to any forward-thinking business looking to capitalise on the latest trends in artificial intelligence.
We believe in a 
results driven approach across all of our AI development services.
There is so much opportunity to increase your business sales, start your journey today.
Contact us50%
Machine learning can reduce supply chain forecasting errors by up to 50%
Cost Reduction
10%
Businesses implementing machine learning observe a 10% increase in sales through more accurate stock and customer demand predictions
Increased Sales
90%
of businesses reported faster complaint resolution
Customer Satisfaction
50%
Machine learning improves the detection of fraudulent transactions by up to 50%
Fraud Detection
40%
AI and ML technologies are projected to increase business productivity by up to 40%
Operation Efficiency
20%
Companies using machine learning for human resources have seen employee engagement increase by 20%
Employee Productivity
Our machine learning development process
01
Planning
Initially we plan a consultation. We discuss the expectations for the project setting up a realising timeline and budget for the goal.
02
Data Preparation
This step may involve setting up data collection mechanisms, ensuring data quality, and preparing datasets for analysis. We also perform initial investigations on the data to discover patterns, spot anomalies, test hypotheses, and check assumptions using statistical summaries and graphical representations.
03
Development
Next, we transform raw data into features that better represent the underlying problem to the predictive models we choose appropriate machine learning algorithms based on the problem type (e.g., regression, classification) and train multiple models to find the best performer.
04
Model Evaluation
We evaluate the model's performance using appropriate cross-validation techniques to ensure the model generalises well to new data.
05
Deployment
Finally, we deploy the machine learning model into a production environment where it can start making predictions or decisions based on new data. We continuously monitor the model's performance to catch any degradation over time.
Want to get a tailored process to your specific needs? Contact us now
Our AI development Insights
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Hear it from our clients: success in their own words
University of Suffolk
Ruth Patron
Centre Manager
&Element created us an immersive brand and brand strategy for Entrepreneurs Forge. The team worked with us through many research rounds to delivery exactly what we wanted.
Cochrane Associates
Dr. Peter Cochrane OBE
Ex-CTO of BT
There is nothing like a change of career for creating a tidal wave of disruption; and after decades of leading industry, I was ready. &Element are the best I have worked with to progress this change, and therefore come with my full support and highest recommendation.
Arma Karma
Ben Smyth
CEO
We worked with &Element to create an engaging pipeline of projects over 12 months for our business. Including a marketing website, 3 customer checkouts and a staff dashboard and API integrations, &Element supported us to achieve this huge feat.
Ballen Studios
Christopher Luich
Head of Operations
&Element have been fundamental to developing our AI dashboard and other machine learning solutions. They have allowed us to achieve huge growth and modernisation in our company. Thank you for your hard work.
Ministry of Defence
Sarah Eshelby
Employability Officer
We approached &Element to build us an employability portal for our tri-service military personnel looking at gaining new skills and career opportunities. They were efficient and helpful throughout the project and we hope to work with them again.
Maekersuite
Stephanie Demetriou
Co-Founder
Thank you &Element for your hard work, professionalism and knowledgeability. Leading us over many years to build out our web dashboards and integrate advanced AI features (such as facial tracking, intelligent teleprompters, data scraping).
Featured AI development case studies
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Our tried-and-tested technology stack for web development projects
React.js Development
Node.js server-side development
Next.js. a react framework
MongoDB, noSQL database
Web Development FAQs
What is machine learning?
Machine learning is a branch of artificial intelligence (AI) that focuses on building applications that learn from data and improve their accuracy over time without being programmed to do so. It involves developing algorithms that can process large sets of data and perform tasks such as predictions, recommendations, and decision making.
01
What does a machine learning developer do?
A machine learning developer designs, builds, and implements machine learning applications according to specific business needs. They are responsible for collecting data, developing and training machine learning models, fine-tuning their performance, and deploying them to production where they can automatically make data-driven decisions.
02
How can machine learning benefit my business?
Machine learning can enhance business operations in several ways, including automating routine tasks, improving customer experience, increasing operational efficiency, and providing insights that help make strategic decisions. It benefits customer segmentation, fraud detection, demand forecasting, and resource optimisation.
03
What industries benefit most from machine learning?
While almost all industries can benefit from machine learning, the most impacted sectors include finance, healthcare, retail, manufacturing, and transportation. In finance, ML is used for algorithmic trading and risk management; in healthcare, for predictive diagnostics; in retail, for personalised customer experiences; and in manufacturing, for predictive maintenance.
04
How long does it take to develop and deploy a machine learning model?
The timeline can vary greatly depending on the complexity of the problem, the amount of data to be processed, and the specific requirements of the project. Generally, a machine learning project can take from a few weeks to several months.
05
What tools and technologies are used by machine learning developers?
Machine learning developers typically use programming languages like Python and R, along with ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. They also utilise various data processing frameworks and platforms like Apache Spark and Hadoop.
06
What data do I need for machine learning?
The data required for machine learning depends on the specific objectives of the project but generally includes a large set of historical data points from which the algorithms can learn. The quality, completeness, and variety of data are crucial factors that affect the outcome of the learning process.
07
Can machine learning be integrated with my existing systems?
Yes, machine learning models can often be integrated with existing IT infrastructure using APIs or middleware. This integration allows businesses to enhance their existing systems with intelligent features such as predictive analytics and automated decision-making.
08
What is the cost of hiring a machine learning developer?
The cost of hiring a machine learning developer varies based on the complexity of the project and the expertise of the developer. If you wish to know more about our pricing we encourage you to contact us.
09
How is machine learning transforming businesses?
Machine learning (ML) is revolutionising businesses by automating data analysis and enabling predictive insights. It helps in improving operational efficiency, enhancing customer experiences, and fostering innovation through data-driven decision-making. ML applications include personalised marketing, fraud detection, and optimising supply chain logistics.
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