Everything You Need to Know About TensorFlow 2.0: A Guide
Artificial Intelligence

Everything You Need to Know About TensorFlow 2.0: A Guide

Recently, Google announced Tensorflow 2.0, an open-source framework for machine learning to help both small and big businesses out there.

According to the recent study conducted by Forbes, it would be safe to assume that AI and machine learning applications will be used more commonly across enterprises and businesses, especially in predictive analysis.

Not just this, machine learning and deep learning aided technologies are being actively integrated into companies to boost customer loyalty, increase profit opportunities, and simplify processes and distribution.

Let’s understand the concept in detail.

What is the TensorFlow?

TensorFlow is the use of artificial intelligence and machine learning in day-to-day life.

In simple words, we can use TensorFlow to access powerful machine learning models that can recognize billions of physical objects and their connections with space.

See more: How the Application of Artificial Intelligence Assists Businesses?

The best thing is that TensorFlow takes this technology to the frontend, which ensures the real-time representation of the real world can now be achieved using the device’s audio-visual receptors from inside a web browser or smartphone app GUI.

TensorFlow for AI and ML

There is no denial in the fact that there are many machine learning solutions and libraries available out there. But the thing about TensorFlow is, it provides an opportunity to newbie developers in the area by providing access to the entire powerful library.

Using TensorFlow the developers don’t have to start everything from scratch. They can easily use this framework to create strong apps by combining their different modules. TensorFlow’s most important feature for machine learning creation is abstraction.

Developers should concentrate on the general logic of the program rather than the nitty-gritty of applying algorithms or working out appropriate ways to hitch the output of one element to the input of another. Behind the scenes, TensorFlow takes care of the data.

TensorFlow technology is used to link the dots in an image, converting it into a particular figure such as a balloon. It functions much like a computer that recognizes the wizard and translates it in a coherent way for humans to understand.

You must have heard about the UK-based company Ocado, which came out open about using TensorFlow technology. They used libraries to execute their routing algorithms, moving through their warehouses with machines, and developing their forecasting capability.

This is just one example, there are a plethora of businesses out there who rely on artificial intelligence services to bring the best out of their service offerings.

Tensorflow For Predictive Analysis: Aiding Real-Time Business Applications

Coming to our next segment, here we are disclosing some use cases of how machine learning solutions help businesses out there.

Read more: Are AI and Cloud Reshaping Enterprise Communications?

Predictive analysis is an important aspect of TensorFlow. In layman’s words, it uses computational simulation, data processing, and artificial intelligence principles to provide observations that assist in predicting future trends. Let’s understand how TensorFlowopens up a world of opportunities for businesses.

  • Agricultural and Food Industry: Agricultural and food industry is the pillar element of any country. This sector needs innovation as it is responsible to provide food to the entire nation.

Machine learning, artificial intelligence service, and the Internet of Things (IoT) work together to identify and eliminate plant diseases. This technology in the agricultural industry will support key decision-making.

Not just this, it will help implement strategic decisions about where to plant that can maximize the possibility of a desirable result and satisfy demand.

If farmers will be aware of what to sow, then it will surely help to meet the growing demands of the population. By computing weather and agriculture databases, predictive analysis allows for the estimation of quarterly and annual crop yields. Predicting potential prices of based goods can be done by forecasting demand and supply for crops in advance. In short, you will get a detailed analysis of crop, demand, and yield.

  • Banking and Finance: Now almost everyone out there uses banking and finance services. What if we say using TensorFlow, you can predict the stock prices?

Yes, it is possible using TensorFlow.

It observes the past behavior of stock prices and then predicts the future pricing. The detailed process involves analyzing previous market results, taking current news about the stock into account, and analyzing opinion correlated with it, as well as many other basic and complicated metrics.

Apart from this, you can detect fraudulent activities too. It keeps an eye on circular trading, which is the practice of buying and selling stock shares in unusual ways within a group of people who are somehow related. Furthermore, you can detect tax invasions by observing past activities and data sets.

  • Pharma and Healthcare: TensorFlow is opening new opportunities in the pharma and healthcare sector as well. It is beneficial and much needed in the health industry.

The technology can help to identify patients with identical symptoms using Machine Learning algorithms on medical databases such as the CLAIMS database.

For example, an ML model can be applied using classification and regression algorithms on data of patients diagnosed with AIDS or Cancer to confirm whether a prospective patient is afflicted with the same.

Furthermore, it offers personalized treatment to patients, which is the need of the hour. Customized medication recommendations based on historical evidence and deterministic outcomes could increase treatment success rates. It’s not only beneficial to patients but also to hospitals in identifying their resources.

Some Companies That Bank On TensorFlow

We have already mentioned Ocado in the above section, the other company that uses TensorFlow technology is Airbnb. It leverages this technology to categorize photos. It is the hub that features millions of homes.

  • Airbus: Airbus, the defense and space service uses this technology to provide insights to its clients. The technology helps monitor the variation in earth surface for urban planning. and much more.
  • Coca-Cola: The other company that did try their hands on TensorFlow technology is Coca-Cola. It helps improve character recognition and also enhances accuracy without any difficulty.

Not just this, it had to deal with a wide variety of product code media, including hundreds of various cardboard fridge-pack media, font styles, bottlecaps, and much more.

  • Intel: Last, we have Intel who joined the race and found out that TensorFlow is providing a deep learning model. It helps in boosting backpropagation efficiency. It also entails a careful combination of cache blocking, data formats, and prefetching that encourage spatial and temporal localization.

Know more: Artificial Intelligence: Expectation and Reality

Final Thoughts

That’s all! Here we have mentioned how TensorFlow is gaining popularity and we are going to see a lot of advancement ahead. In the future, we look forward to Sequence-to-Sequence (Seq2Seq) models, which will be useful for designing human language-related applications of software.

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