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2021 Data Science/MachineLearning Project Deployment Mastery

#artificialintelligence

Then this course is for you!! This course has been practically and carefully designed by industry experts to offer the best way of learning Data Science and Machine Learning the practical way with hands-on projects throughout the course. This course will help you learn complex Data Science concepts and machine learning algorithms the practical way for easier understanding. We will walk you through step-by-step on each topic explaining each line of code for your understanding. There is going to be a lot of fun, excited, and robust projects to better understand each concept under each topic.


Data Science and Machine Learning Project/Deployment Mastery

#artificialintelligence

Then this course is for you!! This course has been practically and carefully designed by industry experts to offer the best way of learning Data Science and Machine Learning the practical way with hands-on projects throughout the course. This course will help you learn complex Data Science concepts and machine learning algorithms the practical way for easier understanding. We will walk you through step-by-step on each topic explaining each line of code for your understanding. There is going to be a lot of fun, excited, and robust projects to better understand each concept under each topic.


Build and deploy machine learning web app using PyCaret and Streamlit

#artificialintelligence

In our last post on deploying a machine learning pipeline in the cloud, we demonstrated how to develop a machine learning pipeline in PyCaret, containerize Flask app with Docker and deploy serverless using AWS Fargate. If you haven't heard about PyCaret before, you can read this announcement to learn more. In this tutorial, we will train a machine learning pipeline using PyCaret and create a web app using a Streamlit open-source framework. This web app will be a simple interface for business users to generate predictions on a new dataset using a trained machine learning pipeline. By the end of this tutorial, you will be able to build a fully functional web app to generate online predictions (one-by-one) and predictions by batch (by uploading a csv file) using trained machine learning model.


Deploy Machine Learning Models on GCP + AWS Lambda (Docker)

#artificialintelligence

In this section I will teach you about what is model deployment basic idea about machine learning system design workflow and different deployment options are available at a cloud level.


How to Deploy a Machine Learning Model for Free – 7 ML Model Deployment Cloud Platforms

#artificialintelligence

I remember the first time I created a simple machine learning model. It was a model that could predict your salary according to your years of experience. And after making it, I was curious about how I could deploy it into production. If you have been learning machine learning, you might have seen this challenge in online tutorials or books. You can find the source code here if you are interested.