ML Model Deployment With Flask On Heroku | How To Deploy Machine Learning Model With Flask | Edureka

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This Edureka video on the "ML Model Deployment With Flask on Heroku" will help you understand the necessary steps involved in the development and deployment of the ML model
00:00:00 Introduction
00:00:50 What is Model Deployment?
00:01:58 Introduction To Flask
00:15:41 Building our Machine Learning Model
00:31:18 Setup & Deploy ML Model on Heroku

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#Edureka #EdurekaMachineLearning #ModelDeployment #Edureka #MachineLearningtutorial #Heroku #PythonTraining #EdurekaTraining

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How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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About the Course

Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.

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Who should go for this course?

The following professionals can go for this course:
1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. Business Analysts who want to understand Deep Learning (ML) Techniques
4. Information Architects who want to gain expertise in Predictive Analytics
5. Professionals who want to captivate and analyze Big Data
6. Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

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Комментарии

Perfect tutorial for Beginners, from scratch to deployment. Flawless Deployment and Execution.

darweshfazila

how did u remove the error: local variable referenced before assignment. Plz answer this .

sumanswaraj

thank u so much sir, u save my project final deployment :)

afickredox

Heroku is not free now we have to pay to use heroku so sad😢,

Anyway thanks for this great tutorial

degoaty

This was amazingly explained, thank you.

rios

sir i facing issue meanwhile deploying ml model via github repository nd that is:there was an issue deploying ur app.view the build log for detail should i do sir plzz repond early plzz sir

allprogramminglanguage

Hello sir could you please tell how can I display pictures on my web application using flask

shwetabhagat

omg loved this video very helpful thanks eureka

vishalbhardwaj

after searching for 3 days i found this video.. couldn't be more happier

ispeakfactslol

I kept recieving an error local variable '''mks'' referenced before assignment how to fix?

zackhilacan

hello sir, can you please share the csv file ?

arnolddumba

Hi sir, can you please share the CSV file ?

jayaprakashmurugan

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