Developing Data Science Projects With Google Colab
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 451 MB | Duration: 53m
Develop fake and real news detection data science projects with just your internet browser
What you'll learn

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How to use Google Colab through your internet browser
How to design a data science project
How to train and evaluate a machine learning model
How to deploy a machine learning model in your application
Requirements
This course is not for complete beginners in data science and machine learning
Familiarity with Python programming
Basic knowledge of statistics and machine learning.
Description
This project is for anyone who wants to develop Data science and Machine learning projects but having limited resources on his computer and limited time. In less than 2 hours, you will learn how to develop and deploy a fake news detection data science project!
In essence, you will learn,
- how to design a real life data science project
- how to get data to train a machine learning model
- how to clean and preprocess your data
- how to create and train a model to learn from your data
- how to evaluate the performance of the trained model
- and finally, how to deploy the model in any real-life application of your choice.
According to wikipedia,
"Google Colaboratory (also known as Colab) is a free Jupyter notebook environment that runs in the cloud and stores its notebooks on Google Drive. Colab was originally an internal Google project; an attempt was made to open source all the code and work more directly upstream, leading to the development of the "Open in Colab" Google Chrome extension, but this eventually ended, and Colab development continued internally. As of October 2019, the Colaboratory UI only allows for the creation of notebooks with Python 2 and Python 3 kernels; however, an existing notebook whose kernelspec is IR or Swift will also work, since both R and Swift are installed in the container. Julia language can also work on Colab (with e.g. Python and GPUs; Google's tensor processing units also work with Julia on Colab."
Who this course is for
Intermediate data science and machine learning enthusiasts/learners
Screenshots