Web, ecommerce & Android app development for Willenhall

Why choose New Media Aid?
We develop complex web apps, Android apps and ecommerce websites and have provided low cost, bespoke app development services since the year 2000 - only 86 miles from Willenhall, Walsall. The development cost of a bespoke Android app, web app or ecommerce website for organisations in Walsall will usually be between £2,000 and £5,000.

We develop bespoke, responsive, mobile-friendly web apps and e-commerce websites as well as cutting-edge Android apps for organisations ranging from multi-national blue chip organisations to SMEs in Willenhall, Walsall.

We keep abreast of all the latest trends and technologies in web app development, ecommerce website design and bespoke Android app development to make sure we offer the most advanced, secure and robust application solutions for our clients in Willenhall, Walsall.


Useful app developers term of the day: Deep Learning

Deep learning is a subset of machine learning that involves the use of neural networks with multiple layers. In deep learning, the neural network is composed of multiple layers of interconnected nodes, which are capable of learning complex patterns in the data.

Deep learning has been particularly successful in applications such as image recognition, speech recognition, and natural language processing, where the input data can have a high degree of complexity and variability.

Some of the key features of deep learning include:

  1. Multiple layers: Deep learning models have multiple layers of nodes, which can learn increasingly abstract and complex representations of the data.

  2. Nonlinear activation functions: The nodes in a deep learning network use nonlinear activation functions, which allow the network to learn complex, nonlinear relationships between the input and output data.

  3. Backpropagation: Deep learning models use a technique called backpropagation to update the weights of the network during training. Backpropagation calculates the gradient of the loss function with respect to the weights of the network, and uses this gradient to update the weights to minimize the loss function.

Deep learning has led to significant advances in many applications, such as image and speech recognition, natural language processing, and autonomous driving, among others. However, deep learning models can also be computationally expensive to train and require large amounts of data to achieve high accuracy.


Deep learning is a subfield of machine learning that involves training neural networks with multiple layers to learn and extract features from large amounts of data. In bespoke app development, deep learning is used to create models that can recognize patterns and make predictions based on large datasets.

A deep neural network is composed of multiple layers of interconnected neurons, each of which performs a specific operation on the input data. The input data is passed through the layers, with each layer building on the features learned by the previous layer to create more complex representations of the input. The output of the final layer is then used to make a prediction or decision.

Deep learning is particularly useful for bespoke app development because it can automatically learn relevant features from raw data, without the need for human intervention or manual feature engineering. This allows developers to create models that can handle complex, high-dimensional data, such as images, speech, and text.

Some common applications of deep learning in bespoke app development include image and speech recognition, natural language processing, and predictive analytics. For example, a deep learning model could be used to analyze medical images and detect signs of disease, or to analyze customer data and make predictions about their behavior.

Overall, deep learning is a powerful technique for creating sophisticated machine learning models that can handle complex datasets and make accurate predictions. With the increasing availability of data and computing power, deep learning is becoming an increasingly popular approach in bespoke app development.



Crimes reported in Willenhall
Our custom app development prices are criminally low, but not as criminal as these events recently reported in Willenhall.

Why are we showing recent crimes in Willenhall Walsall?
We are showing a few example crimes for Willenhall reported in Jan 2024 to demonstrate how we can integrate data from external web service APIs. As expert software engineers we specialise in developing complex bespoke web apps which integrate with other cloud-based systems and data-sets!

bicycle theft
  • Fryers Close (Investigation complete; no suspect identified)
burglary
  • A4124 (Investigation complete; no suspect identified)
  • Fishley Close (Unable to prosecute suspect)
  • Grant Street (Under investigation)
  • Baytree Road (Investigation complete; no suspect identified)
  • Chestnut Road (Investigation complete; no suspect identified)
criminal damage arson
  • Reeves Street (Investigation complete; no suspect identified)
  • Barracks Place (Awaiting court outcome)
  • Bakewell Close (Unable to prosecute suspect)
  • Providence Lane (Investigation complete; no suspect identified)
  • Petrol Station (Investigation complete; no suspect identified)
drugs
  • Elmore Green Close (Under investigation)
  • Harrison Close (Under investigation)
  • Elm Road (Under investigation)
  • Foundry Lane (Local resolution)
  • Elmore Green Close (Unable to prosecute suspect)
other theft
  • Stanley Street (Under investigation)
  • Woodall Street (Investigation complete; no suspect identified)
  • Eagleworks Drive (Under investigation)
  • Baytree Road (Investigation complete; no suspect identified)
  • Dawson Street (Under investigation)
possession of weapons
  • Slacky Lane (Under investigation)
  • Stowe Street (Unable to prosecute suspect)
  • Supermarket (Investigation complete; no suspect identified)
  • Parking Area (Under investigation)
  • Forest Avenue (Under investigation)
public order
  • The Exchange (Under investigation)
  • Wallington Heath (Unable to prosecute suspect)
  • Wye Road (Under investigation)
  • William Wiggin Avenue (Unable to prosecute suspect)
  • Parking Area (Under investigation)
robbery
  • May Street (Under investigation)
  • Millfield Avenue (Under investigation)
shoplifting
  • A34 (Investigation complete; no suspect identified)
  • Parking Area (Under investigation)
  • Odell Crescent (Under investigation)
  • Petrol Station (Unable to prosecute suspect)
  • A34 (Unable to prosecute suspect)
theft from the person
  • Stowe Street (Under investigation)
  • Goscote Lodge Crescent (Under investigation)
vehicle crime
  • Hunter Crescent (Investigation complete; no suspect identified)
  • Parking Area (Investigation complete; no suspect identified)
  • Bloxwich Road (Investigation complete; no suspect identified)
  • Buxton Close (Unable to prosecute suspect)
  • Booth Street (Under investigation)
violent crime
  • Millfield Avenue (Under investigation)
  • Elmore Green Close (Awaiting court outcome)
  • Green Rock Lane (Unable to prosecute suspect)
  • Addenbrooke Street (Unable to prosecute suspect)
  • Ash Street (Unable to prosecute suspect)
other crime
  • Dunlin Drive (Investigation complete; no suspect identified)
  • Goldsmith Road (Under investigation)
  • Mersey Road (Under investigation)
  • Addenbrooke Street (Investigation complete; no suspect identified)
  • Ryle Street (Unable to prosecute suspect)
We are only 86 miles from Willenhall