Categories
Blockchain
Get started
Ecommerce & Digital Marketing
Cloud Computing & DevOps
Get started
Undergraduate Course
Mentor Giri Job Boosters DTGyan Refer & Earn Register Today

Cloud Deployment of Machine Learning Model

The cloud deployment model identifies the specific type of cloud environment based on ownership, scale, and access, as well as the cloud’s nature and purpose. In This course, you would learn the flask app, Heroku, AWS, GCP. DataTrained provides you best in class content by leading faculty. Get an industry-recognized certificate of completion in Cloud Deployment of Machine Learning Model course from DataTrained.

  1. 4.5
  2. (535 ratings)
  • 1100+ Learners
  • English

Cloud Deployment of Machine Learning Model

  1. $6
    • how to deploy machine learning models
    • how to deploy a machine learning model
    • deploy machine learning model
    • model deployment in machine learning
    1100+ Learners
Features
  • 5+ Hours on-demand Video
  • Certificate of completion
  • Projects Included
  • Taught by Industry Pros

What you'll learn

  • flask app
  • Heroku
  • AWS
  • GCP

Syllabus

Best-in-class content by leading faculty and industry leaders in the from of videos, cases and projects, assigments and live sessions

deploy machine learning model flask
deploy machine learning model flask
  • Need to have knowledge on one programming.
  • Need to know Mahine learning
  • Python programming is added advantage.
  • Credit card to create account.
how to deploy machine learning models

The cloud deployment model identifies the specific type of cloud environment based on ownership, scale, and access, as well as the cloud’s nature and purpose. The location of the servers you’re utilizing and who controls them are defined by a cloud deployment model. It specifies how your cloud infrastructure will look, what you can change, and whether you will be given services or will have to create everything yourself. Relationships between the infrastructure and your users are also defined by cloud deployment types.

deploy machine learning model

Get Industry Recognized Certificate of Completion in Cloud Deployment of Machine Learning Model course from DataTrained which can be verified online throughout the world, shared in certification section on your linked profile, downloaded, printed, shared, and mentioned on your resume.

model deployment in machine learning
deploy machine learning model flask Abhay
  1. 4.5

The course is good. It gives a detailed description of sqoop and flume. Every concept is very easy and simple to understand.

how to deploy a machine learning model Raj
  1. 4.5

Instructor has a good command over the subject. Very nicely explained Excellent content, Every Hadoop developer much visit this course even if you are a experience one.

Instructors

Join DataTrained certified curriculum and learn every skill from scratch. Learn Cloud Deployment of Machine Learning Model from the industry’s best thought leaders and upgrade your skills.

Dr. Deepika Sharma - Training Head, DataTrained
Dr. Deepika Sharma
Training Head, DataTrained

Dr. Deepika Sharma has been associated with academics /corporate education for more than 14 years. She has a deep passion in the field of Artificial Intelligence, Data Science, and Machine Learning.

Shankargouda Tegginmani - Data Scientist, Accenture
Shankargouda Tegginmani
Data Scientist, Accenture

Shankar is a data Scientist with 14 Years of Experience. His current employment is with Accenture and has experience in telecom, healthcare, finance and banking products.

Why Take this Course

High-level programming language: With Python, the code looks very close to how humans think. For this purpose, it must abstract the details of the computer from you: memory management, pointers,… Hence, it is slower than “lower-level language” like C;

Python is interpreted and not compiled: Python code is interpreted at runtime instead of being compiled to native code at compile time;

Python is a dynamically typed language: Unlike “statically-typed” languages like C, C++ or Java, you don’t have to declare the variable type like String, boolean or int. The less you do, the more your computer has to work. For each attribute access, tons of lookup is required. In addition, being very dynamic makes it incredibly hard to optimize Python;

Global Interpreter Lock (GIL): This GIL basically prevents multi-threading by mandating the interpreter only execute a single thread within a single process (an instance of the Python interpreter) at a time.

how to deploy a machine learning mode

100% online

deploy machine learning model flask

Global Certification

how to deploy machine learning models

Flexible deadlines