In this, technology-driven world mobile app technology made our lives easier, faster, better and more fun. Technology trends are changing at every second, Machine Learning(ML) is the new-tech wave that has revolutionizing the mobile app world. Today businesses are on the move to mobile apps as it is a highly effective business tool to win the market and outperform competitors.
What is Machine Learning?
Machine Learning is an Artificial Intelligence application that allows a computer program to learn and adapt to new data without human interference.
ML is taking a toll on almost everything around us including robotics, data mining, finance, and e-commerce. As Machine Learning empowers intelligent apps, Mobile App Development Company in Hyderabad who are leveraging this technology trend in app development are in high demand. Let's go over the benefits of Machine Learning app development.
Easy recognition of patterns and trends
Using powerful algorithms ML enables the easy identification of trends and patterns that could have been not possible to humans. Computer vision, speech recognition, Seismic analysis, Radar signal analysis, and face recognition are widely using pattern recognition.
Amazon Lex, Google Cloud AutoML, R-Studio, IBM Watson Studio, Microsoft Azure Machine Learning Studio are some of the tools used for pattern recognition.
Do not require human interference
ML creates trained smart machines rather than programmed with self-learning, improving and decision-making abilities.
Anti-Virus software's are the best examples, they learn to filter new threats as they are recognized.
Personalized Experience
Better personalization is the best way to increase customer loyalty, ROI, and lead generation. Machine Learning helps to obtain details like target audience, kind of budget the majority look for, specific needs, specific app area needs improvement and the keyword used for searches, etc, these allow the business to categorize customers and cater to their needs in a better way.
Continuously improving
ML apps have the ability to self improve from errors, this algorithm continuously understands the errors and resulted in rectification for these errors. With regular error checking it offers the most efficient and accurate data to the users.
Better search
A better understanding of customers makes ML apps possible to throw smart and filtered search results. Cognitive technology helps to categorize videos, documents, and FAQs to provide a best-suited response for search queries.
Enhanced security
The video, audio and voice recognization offers biometric authentication through the ML apps, face detection, fingerprint scanning are the best examples.
The following are some of the machine learning frameworks that can be used to create intelligent apps easily.
- TensorFlow
- CAFFE (Convolutional Architecture for Fast Feature Embedding)
- The Microsoft Cognitive Toolkit/CNTK
- Torch/Pytorch
- MXNet
- Chainer
- Keras
- Deeplearning4J (DL4J)
- Sonnet
- Gluon
- Swift
- ONNX
- Apache Spark
- Scikit-Learn
- Apache Mahout
- Apache Singa
- Amazon Machine Learning
- NET
- Theano
- H2O
- Core ML
- Bender
- Quantized-CNN
- Apache PredictionIO
- Microsoft Distributed Machine Learning Toolkit
- OpenNN
In this new era of intelligent Machine Learning apps potentially revolutionize how the everyday world works. Netflix, Tinder, Oval Money, Snapchat, Google Maps are some trending Machine Learning mobile apps today.
