Étude de marché sur l’apprentissage profond

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

Vous devez répondre à leurs attentes et leur apporter le meilleur soutien possible. C’est là que le besoin de Deep Learning et d’études de marché entre en jeu.

Qu’est-ce que l’apprentissage profond ?

Il existe plusieurs façons de faire apprendre un processus à une machine. L'apprentissage profond est l'une de ces méthodes. Le concept de Deep Learning est également connu sous le nom d’apprentissage hiérarchique ou d’apprentissage structuré en profondeur. Contrairement aux autres processus, la méthode Deep Learning se concentre sur les représentations de données. Vous pouvez superviser le processus d’apprentissage, ou il peut être non supervisé ou semi-supervisé. De nombreux domaines et industries appliquent déjà certaines architectures de Deep Learning, telles que les réseaux de neurones récurrents, les réseaux de croyance profonde et les réseaux de neurones profonds. Ils utilisent les réseaux de neurones pour promouvoir l'apprentissage. Ils peuvent apprendre des tâches complexes et traiter de nombreuses données qui ne seraient pas possibles pour un humain.

Le marché est en croissance

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.

Avantages de l'apprentissage profond

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.

De nombreuses entreprises utilisent le Deep Learning pour comprendre leurs données. Ils l'utilisent également pour cibler des clientèles spécifiques. De nombreuses entreprises l'utilisent également pour la vision par ordinateur, le réglage et l'optimisation.

Comment les entreprises appliquent-elles le 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.

À propos des études de marché sur l’apprentissage profond

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:

• Recherche qualitative: Groupes de discussion avec des data scientists et des clients
• Recherche quantitative: Enquêtes et collecte de données pour algorithmes et traitement de données
• Conseil en stratégie: Market Sizing, Go-To-Market Strategy, Technology Acquisition, and Competitive Analysis