Ricerche di mercato sul deep learning

For your business to grow, you must understand your customers.

Devi soddisfare le loro aspettative e fornire loro il miglior supporto possibile. Ecco dove entra in gioco la necessità del Deep Learning e delle ricerche di mercato.

Cos'è l'apprendimento profondo?

Esistono diversi modi per far sì che una macchina apprenda un processo. Il deep learning è uno di questi metodi. Il concetto di Deep Learning è noto anche come apprendimento gerarchico o apprendimento strutturato profondo. A differenza degli altri processi, il metodo Deep Learning si concentra sulla rappresentazione dei dati. Puoi supervisionare il processo di apprendimento, oppure può essere non supervisionato o semi-supervisionato. Molti campi e industrie applicano già alcune architetture di Deep Learning, come le reti neurali ricorrenti, le reti di credenze profonde e le reti neurali profonde. Usano le reti neurali per promuovere l'apprendimento. Possono apprendere compiti complessi ed elaborare molti dati che non sarebbero possibili per un essere umano.

Il mercato è in crescita

Popular neural networks have around eight layers and 60 million parameters. The Deep Learning neural networks go up to 200 or 400 million settings. The great thing is that the market is growing. Businesses need Deep Learning to study business data, see problems, and identify solutions. Many companies are already accessing their benefits. Deep Learning continues to be very popular in the business world.

Vantaggi dell'apprendimento profondo

One of the main benefits of Deep Learning is that it transforms companies. Based on company data, it’s a lot easier to figure out what’s wrong, what customers expect, and what you need to change. The transformation process is comprehensive and meaningful. It can have a positive effect on your business. By studying company data, Deep Learning also allows markets to be more efficient. It helps a lot, and it delivers a resounding return on investment every time.

Molte aziende utilizzano il Deep Learning per comprendere i dati aziendali. Lo usano anche per prendere di mira basi di clienti specifiche. Molte aziende lo utilizzano anche per la visione artificiale, la messa a punto e l'ottimizzazione.

In che modo le aziende stanno applicando il deep learning?

The oil and gas industry uses Deep Learning to lower its extraction costs. This industry also uses it for locating, delivering, and processing the oil. The construction industry uses Deep Learning to create step-by-step project simulations. With deep learning, it’s easy for builders to see what can go wrong. Also, for cybersecurity, Deep Learning can improve the detection rate for malware. Social media, finance, transportation, healthcare, and many other industries use Deep Learning.

Deep learning will help you understand your business and uncover new opportunities. This method processes a vast amount of data. You can use this data to figure out what approach and system will work for you. You can generate new business opportunities. You may also see some challenges that can arise from your competition. Once you have all that info, you can start speaking to decision makers. They can analyze the data and recommend changes.

While information is everywhere, the main issue is finding the right insights. Companies also need to use data correctly. With help from SIS International, you will find it a lot easier to access deep learning and reach data scientists. You also get consumer research and many other services in a very affordable package. Don’t hesitate! Talk to SIS International today to harness the power of deep learning for your business.

Informazioni sulle ricerche di mercato sul deep learning

SIS is a leading Global Market Research and Strategy Consulting company. We provide data, insights and strategies to gain advantage in today’s fast-paced business landscape.  With data and strategy, companies can better identify opportunities and advantages. Examples of our work include:

• Ricerca qualitativa: Focus group con data scientist e clienti
• Ricerca quantitativa: Indagini e raccolta dati per algoritmi ed elaborazione dati
• Consulenza strategica: Market Sizing, Go-To-Market Strategy, Technology Acquisition, and Competitive Analysis