Global Neural Network Software Market Research Report 2017 to 2021 provides a unique tool for evaluating the market, highlighting opportunities, and supporting strategic and tactical decision-making. This report recognizes that in this rapidly-evolving and competitive environment, up-to-date marketing information is essential to monitor performance and make critical decisions for growth and profitability. It provides information on trends and developments, and focuses on markets and materials, capacities and technologies, and on the changing structure of the Neural Network Software Market.
Companies Mentioned are Hewlett Packard Enterprise Development, IBM, Intel, Microsoft, and Qualcomm Technologies, Alyuda Research, Deep Instinct, Cloudera, Cognisess, Enlitic, GUMGUM, Hu:toma Artificial Intelligence, MulticoreWare, Neurala, NeuroDimension, Palisade, Wave Computing, Ward Systems Group, XENON Systems, and XILINX.
The global Neural Network Software market consists of different international, regional, and local vendors. The market competition is foreseen to grow higher with the rise in technological innovation and M&A activities in the future. Moreover, many local and regional vendors are offering specific application products for varied end-users. The new vendor entrants in the market are finding it hard to compete with the international vendors based on quality, reliability, and innovations in technology.
Major points covered in Global Neural Network Software Market 2017 Research are:-
- What will the market size and the growth rate be in 2021?
- What are the key factors driving the global Neural Network Software market?
- What are the key market trends impacting the growth of the global Neural Network Software market?
- What are the challenges to market growth?
- Who are the key vendors in the global Neural Network Software market?
- What are the market opportunities and threats faced by the vendors in the global Neural Network Software market?
- Trending factors influencing the market shares of the Americas, APAC, and EMEA.
- What are the key outcomes of the five forces analysis of the global Neural Network Software market?
This independent 86 page report guarantees you will remain better informed than your competition. With over 150 tables and figures examining the Neural Network Software market, the report gives you a visual, one-stop breakdown of the leading products, submarkets and market leader’s market revenue forecasts as well as analysis to 2021.
Geographically, this report is segmented into several key Regions, with production, consumption, revenue (million USD), and market share and growth rate of Neural Network Software in these regions, from 2012 to 2021 (forecast), covering Americas, APAC and EMEA.
The report provides a basic overview of the Neural Network Software industry including definitions, classifications, applications and industry chain structure. And development policies and plans are discussed as well as manufacturing processes and cost structures.
Then, the report focuses on global major leading industry players with information such as company profiles, product picture and specifications, sales, market share and contact information. What’s more, the Neural Network Software industry development trends and marketing channels are analyzed.
Commenting on the report, an analyst from MIR’s team said: “One trend in the market is increasing emergence of neural networks in different sectors. The neural network analysis of environmental concerns such as air pollution, emission inventory, and pollutant dispersion is growing at the global level. A neural network‐based scheme is suggested and applied to site‐specific short and medium‐term forecasting of ozone concentrations.”
According to the report, one driver in the market is rising demand for prediction tools. For many industries globally, the demand prediction is an important component of planning resource allocation, scheduling maintenance tasks, optimizing logistics, and having well-informed supply and pricing decisions. Highly accurate forecasts are crucial to avoid unnecessary costs and service disruptions. A prediction tool needs to be aligned with business goals and also with all of the other processes of companies.
Further, the report states that one challenge in the market is increasing availability of open-source neural network software. With innovative advances, a few open-source solutions have shown up, posturing solid competition for neural network software. Open-source neural network software is posing a serious threat to on-premises and cloud-based neural network software market. It can be downloaded and run on all platforms. It is gaining high popularity in developing countries such as India and China.
The study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market and vendor landscape in addition to a SWOT analysis of the key vendors.
The research includes historic data from 2012 to 2016 and forecasts until 2021 which makes the reports an invaluable resource for industry executives, marketing, sales and product managers, consultants, analysts, and other people looking for key industry data in readily accessible documents with clearly presented tables and graphs. The report will make detailed analysis mainly on above questions and in-depth research on the development environment, market size, development trend, operation situation and future development trend of Neural Network Software on the basis of stating current situation of the industry in 2017 so as to make comprehensive organization and judgment on the competition situation and development trend of Neural Network Software Market and assist manufacturers and investment organization to better grasp the development course of Neural Network Software Market.
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