TensorFlow Interview Questions
Self-paced videos, Lifetime access, Study material, Certification prep, Technical support, Course Completion Certificate
Uplatz
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Overview
Uplatz provides this in-depth course on TensorFlow Interview Questions. It is a self-paced course consisting of video tutorials. You will be awarded Course Completion Certificate at the end of the course.
This course by Uplatz focuses on commonly asked interview questions on TensorFlow. It is a self-paced course consisting of video tutorials.
These TensorFlow Interview Questions have been designed specially to get you acquainted with the nature of questions you may encounter during your interview for the subject of TensorFlow. Normally questions start with some basic concept of the subject and later they continue based on further discussion and what you answer.
In this TensorFlow Interview Questions course, you will find a list of top frequently asked TensorFlow Interview Questions and Answers. TensorFlow is made up of two words Tensor and Flow; a tensor is known as data representation for multi-dimensional array and flow means a series of operations performed on tensors. Now we will cover some of the important and most frequently asked TensorFlow interview questions and answers. These TensorFlow Interview Questions will help both freshers and experienced to crack TensorFlow Interview.
Curriculum
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Description
TensorFlow is a Python-friendly open source library for numerical computation that makes machine learning faster and easier. TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.
Originally developed by researchers and engineers from the Google Brain team within Google's AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.
Who is this course for?
Everyone
Requirements
Passion to learn and succeed!
Career path
- Machine Learning Engineer
- Data Scientist - NLP/TensorFlow
- Deep Learning Engineer
- General Analytics Engineer - Machine Learning
- Software Engineer - Python/TensorFlow
- Senior Data Scientist - Machine Learning/TensorFlow
- Python Developer - TensorFlow
- Data Analyst/Consultant
- AI/ML Developer
- Deep Learning Specialist Data Scientist
- Deep Learning Specialist
- Machine Learning Engineer - Computer Vision
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