How easy is it for you to find similar titles on Netflix by typing one keyword? Did you also notice how you look for one product on Amazon, and the next day, your page is filled with related products? Is this all a coincidence? Not really.
Here we call it Machine Learning (ML). The magic behind your everyday convenience, which at times is taken for granted, is the concept of machine learning. Everything from voice navigation to personal assistants like Siri and Google comes out of this phenomenon. So, what exactly is Machine Learning? Why do companies prefer AI JavaScript libraries to run their modern applications? Let’s take a look to know why.
What is Machine Learning?
Machine learning is basically a subset of artificial intelligence(AI) that facilitates the intelligence of any system to analyze and optimize processes without being programmed consistently. The concept takes support from statistics, data, trial and error methods to adapt to a specific task without being coded to perform the same job every time.
Web Applications, JavaScript and Machine Learning:
Web applications are the next-gen future of creating innovative, intelligent and modern solutions to gain customer’s interest. Speaking of which, more than 70% of enterprises prefer developing their websites and applications using JavaScript.
Javascript is ranked the most as the most used programming language for the eighth consecutive year. The language is not only a winner in the frontend but also in server, mobile and desktop development. Currently, JS is used by 94.5% of the entire website. It helps web developers to make web pages interactive and dynamic by custom client-side script implementation.
But today, we need our applications to be future-ready. Applications that are well versed in machine learning and artificial intelligence to stand apart in the competition-driven market. Don’t you think we’d require AI/ML-powered libraries to create such applications? If yes, you are in for a treat.
The top 3 AI/ML-powered libraries for JavaScript that are going to rule 2021:
TensorFlow
TensorFlow is a well-known end-to-end open-source machine learning platform. It is also a JavaScript library that trains and deploys deep learning models in browsers. This ML JavaScript library focuses on creating machine learning models for desktop, mobile, web and cloud. TensorFlow is a data flow programming library at its core. It takes advantage of specific optimization techniques to make accessible expressions and mathematical calculations.
Key features of TensorFlow:
- High scalability
- You can execute the same code on both architectures through CPU/GPU.
- Excellent support for machine learning concepts and deep neural networks.
- Efficient multidimensional expression flow.
Key use areas :
- Voice recognition
- Flaw detection
- Sentiment analysis
- Voice search
- Smart reply
- Text-based applications
- Security/ airports
- Real-time motion detection
BrainJS
BrainJS is a GPU accelerated library that consists of several neural networks. It is a JavaScript written base to perform computations using GPU and is super easy to use. In case GPU is not available, the library falls back to pure JS. One prominent feature of BrainJS is to perform multitasking due to the presence of neural networks.
Key features of BrainJS
- It can develop a simple neural network in a high-level language supporting huge open-source JavaScript libraries.
- Apart from this, one can also make various networks such as - Long short term memory NN, FeedForward NN, Recurrent NN etc.
Key Use Areas:
- Ad placements
- Node application development
- Building/ training neural models
- Character recognition
- In-browsing game applications
ConvNetJS :
ConvNetJS is also a JavaScript written library specialized for deep learning models in the browser. This library allows developers to solve and formulate neural networks in JS without software dependency. Now, isn’t this amazing? All you require is a browser to connect several modules to the layers and Voila! You get your AI/ML transitioned model.
Key features of ConvNetJS
- Support for experimental reinforcement learning modules. These modules are currently based on deep Q learning.
- Facilitates training and specification of convolutional networks to process media.
- Regression and classification soft functions.
Key use areas:
- Neural net classification
- Training and development of reinforcement of learning agents.
- Training and development of the convolutional network.
Final Words
The above mentioned are the top three AI/ML libraries to enhance the JavaScript capability and implement new modes of machine learning in your application development. So when are you going to hire JavaScript developers for your next revolutionary modern application?
April 29, 2020 — Global Camera Module Market is estimated to reach USD 61.78 billion by 2022 owing to the increase in demand for smartphones, tablets, digital cameras and PC devices.
A camera module is an image sensor with integrated control electronics, lens and an interface like Camera Serial Interface (CSI), Ethernet or plain raw low-voltage differential signaling.
It provides functions for clicking photos with the help of electronic devices like smartphones and tablets.
Another factor responsible for the growth of camera module market is the machine vision technology which helps in positioning, measurement, identification, verification and in-flaw detection in numerous industries.
Global Camera Module Market Research Report includes In-depth Analysis of industry by recent technologies, trends, opportunities, challenges, key players and business strategies considering types, segment, and future analysis.
The Camera Module Market Report Provides Growth History, Sales Channel, Manufacturers Profiled in Camera Module Business, Market Share of Product, Application and Regional Scope of Camera Module which makes the research report a helpful resource for marketing people, forecasters, industry executives & consultants, sales, product managers, Strategy Advisor, potential investors to understand the present as well as future market size, situations in terms of growth rate and revenue.
QuickBooks Error -6000 -77 is an update error that takes place when you have some error updating QuickBooks Desktop.
This is an error that falls in the 6000 series.
"Global non-destructive testing equipment market size was evaluated at $7.53 billion in 2018, and the opportunities in the same are projected to rise at a healthy compound annual growth rate (CAGR) of 6.98% during the forecast period of 2019 to 2025.
As per a research report released from IndustryARC, the global non-destructive testing equipment market size was evaluated at $7.53 billion in 2018, and the opportunities in the same are projected to rise at a healthy compound annual growth rate (CAGR) of 6.98% during the forecast period of 2019 to 2025 as mentioned in a recent business intelligence report by IndustryARC’s market analyst.The report is titled “Non-Destructive Testing (NDT) Equipment Market: By Industry (Aerospace, Automotive, Power Generation, Others) By Application (Flaw Detection, Dimensional Measurement, Others) By Technology (Ultrasonic, Magnetic Particle, Others) & Geography – Forecast (2019 - 2025).” The report contains comprehensive insights related to trends, outlook, demands, forecast, geographical distribution, market share by top 5 companies and market size by the startups during the forecast period .
This report covers Non Destructive testing equipment market Size by Product and applications, Non Destructive testing equipment market share by top 5 companies and also the market share by start-ups during the forecast period.View Full Table Of Non Destructive Testing Equipmenthttps://www.industryarc.com/Report/190/non-destructive-testing-equipment-market.htmlReport Price (Single User): US $3850Global NDT Equipment Market: Leading SegmentsNorth America is the directing leader in the global non-destructive testing market.
Ensuring stability and quality in such infrastructures is paramount for public safety.
Profits in the healthcare sector are recurring owing to the widespread of the newer disease every now and then.
Other than the healthcare industry, the construction industry is mandatorily using the non-destructive testing to ensure the stability, robustness, and rigidity of infrastructure.According to the World Bank Group, 75% of the infrastructure that will be present in 2050 is yet to be constructed, and there is a lot of investment gap that will be filled in the coming years which will propel the demand in the NDT equipment market.
