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Top 3 Machine Learning Softwares for Developers

Jan 10th 2019 at 3:06 AM

Machine learning and artificial intelligence are the new hot career areas in IT and development organizations, Machine Learning and AI are an effective way of expanding your business and taking it to a new level. Machine learning is used when making programs and algorithms and It is used in Search engine, spam detection ,data mining and character recognition.





To learn more about Machine learning, Check out the Updated Machine learning Topics

How can you benefit from machine learning?

Have you been collecting big data on your customers but don’t know how to make sense of it? Machine learning will enable you to determine patterns in your customers’ buying behaviour. The possibilities of machine learning are endless. It is the future of software development. Machine learning can produce high value predictions that can help you make better business decisions, in turn leading to reduced costs and increased revenue. Here are the list of  best machine learning tools,
  • Tensorflow
  • Apache Spark
  • Scikit-learn

1. Tensorflow
Tensorflow  is an open source software library for machine learning. It was developed by the Google team for sorts of perceptual tasks. Also, to conduct sophisticated research on machine learning and deep neural networks. Features of Tensorflow
  • TensorFlow enables users to write their own higher-level libraries on top of it by using C++ and Python. Also, express the neural network computation as a data flow graph.
  • It can run on varied CPUs or GPUs, and even on mobile computing platforms. It also supports docker and running via the cloud.

2. Apache Spark MLlib
Apache Spark MLlib is a machine learning library. It’s primary objective to make practical machine learning easy and scalable. Also, it includes classification, clustering, regression collaborative filtering and dimensionality reduction. Features of Apache Spark MLlib
  • We achieve a high data processing speed of about 100x faster in memory and 10x faster on the disk. This is made possible by reducing the number of read-write to disk.
  • We can reuse the Spark code for batch-processing, join stream against historical data or run ad-hoc queries on stream state.
  • Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud, against diverse data sources

3. Scikit-learn
Scikit-learn is a library used to perform machine learning in Python. Scikit learn is an open source library which is licensed under BSD and is reusable in various contexts, encouraging academic and commercial use. It provides a range of supervised and unsupervised learning algorithms in Python. Features of Scikit-learn:
  • Simple and efficient tools for data mining and data analysis. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means, etc.
  • Accessible to everybody and reusable in various contexts.
  • Built on the top of NumPy, SciPy, and matplotlib.
  • Open source, commercially usable – BSD license.
Conclusion

These top 3 machine learning softwares mentioned above are the top most used and has number of job opportunities for it since many organizations are opting for it. Learning the tools professionally from a best Machine learning training institute in India will help you learn the tools from scratch to all the advanced topics. best machine learning softwares | machine learning tools | best machine learning frameworks | artificial intelligence and machine learning course in chennai | top institutes for machine learning in chennai
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