4 Key Skills That Complement Deep Learning Technology!
Deep learning is a part of machine learning technology, which deals with algorithms inspired by the structure and function of the brain called artificial neural networks. It is the technology behind driverless cars and voice control in consumer devices. Deep learning allows computers to perform classification tasks directly from images, text, or sound, achieving accuracy and efficiency. A large set of labeled data and neural network architectures are used to train models and exceed human-level performance. By attaining impressive results, deep learning helps businesses to meet customers’ expectation. Deep learning online training programs are designed to aim at individuals who want to master deep learning concepts and transform into deep learning experts.
See Related: – Learning Path for Deep Learning!
Global enterprises are leveraging deep learning technology and empowering their workforces to take full advantage of its numerous benefits. They seek professionals who own technical skills and understand how to build neural networks, and know-how to lead successful deep learning projects. Multisoft Virtual Academy offers deep learning online courses that are exclusively designed by industry experts and comprise both practical and theoretical learning sessions so that participants make the most of their time and effort. To know more about deep learning courses.
For deep learning professionals, some of the key skills that would complement their existing skills are listed below.
Mastering deep learning with TensorFlow, which is an open-source software library for dataflow and differentiable programming, allows professionals to apply this advanced technology to unstructured data, including images, sound, and textual data, to solve real-world problems. Since deep learning models that use TensorFlow are used in industries, such as healthcare and agriculture, professionals with TensorFlow skills are hired by organizations to help them find solutions to various business challenges.
NLP-based models are used in a wide range of applications such as Google’s search engine and Amazon’s voice assistant, Alexa. When it comes to teaching machines the ability to perform complex natural language-related tasks, NLP-based systems achieve superior results. According to Monster.com, NLP is one of the most sought after skills along with deep learning and machine learning.
RPA, which automates business workflows and clerical processes, is optimized for some GUI (Graphical User Interface) actions by applying deep learning algorithms. Integrating RPA with deep learning gives intelligent automation solutions. Since the global market for RPA reached $271 million in 2016 and is expected to grow to $1.2 billion by 2021, learning deep learning with RPA can help aspirants accelerate their professional growth.
Since data science professionals own good and extensive experience in math, calculus, and statistics, it becomes fairly easier for them to get started with deep learning. Data scientists need to be updated with the latest theories, technologies, and frameworks. Learning GUIs and AutoML helps data science professionals to get more productive and solve more problems.
Summary: This blog talks about 4 different skills that help deep learning professionals make the most of their expertise and experience.
