// Hire
Neural Network Developers | Hire Neural Network Development Company
// Hire
Neural network developers are one of the most in-demand professionals in the informational technology industry. Millions of employers search for talent and offer large salaries, yet since there is a lack of specialists in IT, hiring a good professional is not easy. This article will explain what skills and knowledge must neural network developers have and where to find them.
Neural networks (NNs), also known as artificial neural networks (ANNs), are the most successful implementation of artificial intelligence that employs the biological neural network organization and functioning principles. Hence, they imitate the human brain. NNs use mathematical models that replicate the functions, structure, and connection of biological neurons and neural networks; thus, the computer can learn and make conclusions like a human.
What can neural networks do?
Teaching artificial neural networks for this purpose will require many images with and without animals in different variations, locations, backgrounds, appearances, etc.
eCommerce. Neural networks are most widely standard in online shops that analyze our former queries and personal data to provide recommendations, products, or even special personalized sales (a popular means in mobile and video games). Furthermore, NN also optimizes publications, making images and 3D models for products. Chat or audio bots on neural networks facilitate communication with clients.
Retail sales. The neural networks optimize sales chains and logistic channels, fight fraud and thefts, count the products on shelves in shops and warehouses, enhance marketing, and many others. Smart Walmart store in Levittown, New York, where AI on a neural network tracks the supply of products and due date, is an excellent example. Furthermore, Artificial intelligence by Walmart supervises sellers and clients to prevent thefts, fraud, and other violations.
Finances and banking. This industry uses neural networks to analyze, forecast, and fight fraud. SAS Real-Time Decision Manage software helps banks decide whether to issue a loan. NN Finprophet forecasts market direction for fiat, crypto, and stocks. Citibank developed artificial intelligence for preventing fraudulence with bank cards. JPMorgan Chase uses neural networks to optimize document flow, analyze markets and follow KYC/AIM regulations.
Automotive industry. Artificial neural networks optimize and automatize processes, from creating new autos to managing the mechanisms that make cars. Moreover, NNs in the automotive sector also are autopilots; for instance, AI by Tesla. These solutions are not perfect, yet shortly NNs will drive all cars since it is cheaper and more secure.
Insurance. Insurance companies often use neural networks to forecast the loss coefficient, reveal fraud schemes, adjust bonuses, etc. NN Allstat analyses data about each driver and offers personalized insurance rates depending on their inclination to accidents.
Logistics. Neural networks cover almost all processes here, from building optimal delivery routes to managing drones and assigning people for work positions based on their skills and experience. Amazon and ETA Windward Maritime have excellent platforms that employ AI by Fourkite, and AI on neural networks do almost all job.
Data. The essential element for neural network development is the need for massive data to teach the network. For instance, if you want to create a neural network that will identify people on photos, you will need hundreds of thousands, if not millions, of images with people. Suppose you want to make an application that will forecast the financial markets. In that case, you will need historical data or integration with an aggregator that collects information on these financial markets in real-time.
Collecting information for images and financial markets is relatively easy, while collecting data for other instruments will be hardly possible or complex. For example, you are unlikely to collect much data on accidents and even less on explosions of massive stars in our galaxy. In such cases, you will either have to use synthetic data to train Neural Network or give up on NN.
The process of developing neural networks. Creating and teaching artificial neural networks is a complicated process that requires a lot of time and investment. However, some libraries (NeuroLab, ffnet, SciPy, TensorFlow, Scikit-Neural Network) facilitate the process. Yet, they are applicable only for a limited number of scenarios and often will not suffice for creating unique solutions that focus on a particular business.
Here is a straightforward algorithm that will help you find the best neural network developer to launch your project regardless of the level of complexity and specification.
The task: make a list of 20-50 companies that you could select for developing a neural network model.
The process: scan Facebook, LinkedIn, and Clutch.co, Goodfirm.co, Upwork, Toptal, and other platforms for companies that work with neural network development. You may ask your colleagues or partners whether they know of such a company. See who has developed the NN for your competitors. You must focus on finding a company that specializes in your industry instead of just good developers. For instance, if you plan to develop a cryptocurrency wallet or exchange, you will need an experienced technical partner in cryptocurrency and blockchain, like Merehead.
Task: reduce the long list to 5-10 companies.
The process: contact your long-listed candidates via telephone, messenger, or email. Usually, the response via messenger will come in an hour, while email takes a day. If the wait time is longer, it typically indicates poor communication with customers, creating many problems in the neural network development process.
During the first conversation, you will be asked about your project: what you require the neural network for, your business goals and objectives, the target audience, and so on. Next, the developer should say whether they can cover your need and confirm it with similar projects in their portfolio and the high expertise of their development team. Based on this conversation, you can weed out candidates who don't fit your requirements.
Here are some tips to help you:
The process: After you have examined the offers, you arrange with the candidates to present their offers: how they see your project, how they will achieve your business goals and objectives, for what money, and in what time frame. The presentation usually takes about 30 minutes, with another hour or an hour and a half for follow-up questions and answers. If the project is complex and non-standard, the presentation can be conducted in several stages, and the developer can change his commercial proposal; this is a usual practice.
The task: start developing the neural network.
The process: you make your final choice, go through the conditions once again, sign the contract, and, if necessary, the non-disclosure agreement. Then the technical partner will initiate the development and teaching process for the artificial neural network. The article ‘How to implement neural networks into a business’ explains this process in detail.
Our company offers extensive services for developing artificial intelligence on machine learning and neural networks, from chatbots for online stores to instruments that help to analyze and forecast financial markets. Contact us via +1-206-785-16-88 or sales@merehead.com. Our consultants will tell you the details of neural network development and answer all your questions.
We will be happy to cooperate with you!
Startups fail in 2022