Deep Learning with Tensorflow bootcamp

his course explores, with specific examples, the application of Tensor Flow to the purposes of image recognition


Deep learning is not an entry-level subject. In order to get the most out of the course, students should be familiar with the following:

Basic statistics

Basic linear algebra (matrix multiplication, transposing matrices)

Basic calculus (derivatives, summations)

Programming: Python preferred, but those comfortable with another language should be able to learn the material

There will be a pre-course workshop to refresh students on the requisite linear algebra and calculus techniques. Students with familiarity with NumPy will find it easier to pick up the material, but necessary components will be taught along with the rest of the course. Course materials will be hosted on GitHub, so knowledge of the bash console, Git, and the GitHub platform are beneficial, but not required.


This course is intended for engineers seeking to utilize TensorFlow for the purposes of Image Recognition

After completing this course, delegates will be able to:

  • understand TensorFlow’s structure and deployment mechanisms
  • carry out installation/production environment/architecture tasks and configuration
  • assess code quality, perform debugging, monitoring
  • implement advanced production like training models, building graphs and logging.

The Tensorflow Image Recognition Average Salary Is Est.: $1,50,000 — $2,00,000

Main Office: 1250 Connecticut Ave NW, Washington, D.C 20036

Phone: 202–897–1944 | 202–897–1966

For Training —

For Consulting-

Source: Deep Learning on Medium