AccountIcon BigDataIcon BlogIcon default_resource_icon CartIcon checkmark_icon cloud_devops_icon computer_network_admin_icon cyber_security_icon gsa_schedule_icon human_resources_icon location_icon phone_icon plus_icon programming_software_icon project_management_icon redhat_linux_icon search_icon sonography_icon sql_database_icon webinar_icon

Search UMBC Training Centers

Big Data Analytics

Deep Learning with TensorFlow

+ View more dates & times
  • Overview

    TensorFlow is an open source machine learning library from Google designed for numerical computation using data flow graphs. Nodes represent mathematical operations, while edges in the graphs represent tensors being passed between nodes. While this framework lends itself particularly well to deep learning with neural networks, any framework can be added to the graph, allowing for extreme flexibility.

  • Who Should Take This Course

    AUDIENCE

    This course is for Python programmers and data analysts who want to learn more cutting edge machine learning techniques.

    Prerequisites

    Students should have basic experience with Python.

  • Schedule
  • Course Outline
    • Machine Learning review
    • The data flow graph and how it works
    • Linear regression with stochastic gradient descent
    • Simple neural networks
    • Multi-layer networks
    • Convolutional neural networks
    • Deep learning models for text
  • FAQs
    Is there a discount available for current students?

    UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Online courses are excluded from this offer.

    What is the cancellation and refund policy?

    Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.

Contact Us