Three-Project Series

End-to-End Machine Learning for Rain Prediction

In this multi-part liveProject series, you’ll harness the power of machine learning to make predictions about future rainfall. The Weather Department of Australia is having trouble handling meteorological data manually, and your challenge is to build an end-to-end machine learning model that can make on-the-fly predictions. You’ll use common Python data tools to clean and classify your dataset for analysis, train and evaluate your model, and then deploy your model to a remote server using Flask and Heroku. Work from beginning to end, or dive into whichever section will best augment your skills.

These projects are designed for learning purposes and are not complete, production-ready applications or solutions.

here's what's included

Project 1 Train a Binary Classifier
In this liveProject, you’ll explore a pre-made dataset of meteorological records. You’ll learn the shape, size and type of data at hand, and discover factors that affect rainfall. You use scikit-learn and logistics regression to make initial predictions about future rainfall, evaluate their accuracy, and visualize emerging patterns using Seaborn and Matplotlib.
$29.99 $19.99
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Project 2 Evaluate a Binary Classifier
Judging the effectiveness of a machine learning model requires in-depth analysis. This quick liveProject builds on the work you have completed in Machine Learning for Classification. You’ll assess your early models and consider better alternatives. You’ll plot the ROC curves of the model and compare it to multiple dummy models, and tune your hyperparameters to deliver the most accurate results possible.
$29.99 $19.99
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Project 3 Deploy a Predictive Model
In this liveProject, you’ll deploy a machine learning model to production so it can be easily used by colleagues. You’ll create a virtual environment for deploying your application, use Flask to build a local web service that returns predictions, and Heroku for remote deployment.
$29.99 $19.99
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project author

Harshit Tyagi
Harshit Tyagi has helped over a thousand students master the fundamentals of programming and data science. In his roles at OpenClassrooms and Coding Ninjas, he leverages his technical expertise to conduct workshops and help students bring their course projects to the finish line. He also has a YouTube channel, where he covers fundamental concepts in data science and Python, interview tips, and more. In addition to focusing on data science education, Harshit has developed data processing algorithms with research scientists at Yale, MIT and UCLA.


This liveProject series is for Python data scientists who want to expand their machine learning capabilities. To begin this liveProject you will need to be familiar with:

  • Intermediate Python
  • Basics of pandas
  • Basics of NumPy
  • Basics of Matplotlib
  • Basics of Seaborn
  • Basics of scikit-learn
  • Basics of machine learning
  • Basics of logistic regression

you will learn

In this liveProject series, you’ll learn all the skills you need to develop and evaluate a machine learning model, and then effectively deploy it to production.

  • Manipulating data and exploratory analysis
  • Imputing missing values, engineering outliers, and one-hot encoding
  • Evaluating predictions, accuracy, and other metrics
  • Visualizing patterns with correlation pair plots and heatmaps
  • Hyperparameter tuning with classes and other methods
  • Creation and maintenance of a virtual environment
  • GET and POST requests
  • Creating a web framework for your weather prediction application
  • Saving and loading of sklearn objects
  • Remote deployment on Heroku


You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
includes 3 liveProjects
liveProject $49.99 $59.99 self-paced learning