Deploying a Machine Learning Model using Flask for beginners

The deployment of the machine learning model is rarely discussed. Most of the data science programs, online courses do not focus on model deployment. It is one of the important and last stages in the machine learning life cycle. To start using your machine learning model for practical decision-making, it needs to be effectively deployed into production. The focus of this article is to deploy a machine learning model using a flask.

Here I am using mall customer dataset to understand customer behavior. We are going to build a clustering model on historic data. Using this model we can predict the behavior of the new customer.

Let’s build our model using k-means clustering.

  1. Import Libraries

We need to import all the required libraries

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2. Get the data

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Getting the dataset is not enough. We have to perform exploratory data analysis.

#data #machine-learning #data-science #flask

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Deploying a Machine Learning Model using Flask for beginners
Michael  Hamill

Michael Hamill

1617331277

Workshop Alert! Deep Learning Model Deployment & Management

The Association of Data Scientists (AdaSci), the premier global professional body of data science and ML practitioners, has announced a hands-on workshop on deep learning model deployment on February 6, Saturday.

Over the last few years, the applications of deep learning models have increased exponentially, with use cases ranging from automated driving, fraud detection, healthcare, voice assistants, machine translation and text generation.

Typically, when data scientists start machine learning model development, they mostly focus on the algorithms to use, feature engineering process, and hyperparameters to make the model more accurate. However, model deployment is the most critical step in the machine learning pipeline. As a matter of fact, models can only be beneficial to a business if deployed and managed correctly. Model deployment or management is probably the most under discussed topic.

In this workshop, the attendees get to learn about ML lifecycle, from gathering data to the deployment of models. Researchers and data scientists can build a pipeline to log and deploy machine learning models. Alongside, they will be able to learn about the challenges associated with machine learning models in production and handling different toolkits to track and monitor these models once deployed.

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Justice  Reilly

Justice Reilly

1595294400

Deploying Machine learning models using Flask on your website

Understanding of Machine Learning using Python (sklearn)
Basics of Flask
Basics of HTML,CSS

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sophia tondon

sophia tondon

1620898103

5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

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Ray  Patel

Ray Patel

1625843760

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

  • revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
  • microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
  • Anaconda 4.2 – Anaconda is an opensource Python package

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Nora Joy

1604154094

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