This test evaluates candidates’ technical knowledge of TensorFlow. The test will help identify developers who are proficient in TensorFlow and are capable of implementing various deep-learning models with that framework.
Advanced TensorFlow functionalities
Convolutional neural network architecture with TensorFlow
Complex neural architecture with TensorFlow
Deep-learning engineers, machine-learning engineers, artificial intelligence engineers, data analysts, and any other roles requiring an intermediate knowledge of TensorFlow.
TensorFlow is an open-source machine-learning library for Python, developed and maintained by the Google Brain team. It is widely used for developing and training deep-learning models and is designed to be easy to use and flexible, with a focus on providing strong support for training and inference on graphical processing units (GPUs).
TensorFlow makes it easy to implement complex models, such as those with branching or loops, and it also makes it easier to debug and optimize TensorFlow code. It also includes many high-level libraries and tools for tasks such as natural language processing and computer vision, as well as a number of pre-trained models that can be fine-tuned for a variety of tasks.
Hiring someone experienced with TensorFlow can help your business build and train deep-learning models more quickly and efficiently, reducing the time and resources required to develop machine-learning-based solutions. An experienced TensorFlow developer will know how to design and train deep-learning models that achieve good performance and help to improve the accuracy and effectiveness of a machine-learning system.
TensorFlow's dynamic computational graph allows for greater flexibility in model design and training, making it easier to adapt machine-learning systems to new tasks or changing requirements or to integrate them with other tools and platforms.
This test covers the fundamentals of TensorFlow, advanced TensorFlow functionalities, and working with convolutional neural network architecture and complex neural architecture in TensorFlow. Candidates who perform well on this test will have a strong grasp of core TensorFlow functionalities and be able to make the best use of each one when working with different types of models.
This test will help you hire candidates with the TensorFlow skills necessary to help your company train large or complex machine-learning systems that are easy to deploy and maintain.
Gary has been working in the data science field for more than three years and is proficient in the fields of machine learning and data analysis. He has a Bachelor’s degree in Economics and a Master’s degree in Computer Science. The combination of those two fields helps Gary to achieve even greater results.
He is fond of computer science and loves to work on projects related to Artificial Intelligence which is, in his opinion, the future of our world.
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