How to use Python Pandas for loading dataset
Creating the model in Supervised machine learning
Use pickle to dump the model and vectorizer in the disk
Deploy machine learning model on Django
Requirements
- Python, Django And Machine Learning Basics
Description
Become Artificial Intelligence Engineer.
This is a step-by-step course on how to create book classification using machine learning. It covers Numpy, Pandas, Matplotlib, Scikit learns, and Django, and at the end predictive model is deployed on Django. Most of the things machine learning beginners do not know is how they can deploy a created model. How to put created model into the application? The training model and get 80%, 85%, or 90% accuracy does not matter. As Artificial Intelligence Engineer you should be able to put created model into the application.
Actually, learning how to deploy a Machine Learning model created by machine learning is a big win for you and is a motivating effect towards improving, embracing, and learning machine learning. The piece me off when I hear people saying Artificial Intelligence is not really. It is just a theoretical study. Let’s learn together how to deploy models, solve people’s problems and change people’s minds about Artificial Intelligence.
At the end of this course, you will become Artificial Intelligence by your ability to put created models into the application and solve people’s problems. Not only that you will be exposed to a few concepts of Django which are Python web framework and current trending web framework. By understanding Django, you will be able to deploy the previously created model you could not in the previous time.
Who this course is for:
- Python Developers interested with machine learning
Course content
