Welcome to Notebooks AI! ππππΊπΎΒΆ
A FREE online Data Science environment. Check out all these amazing features π
All libraries already installedΒΆ
pandas
, check βseaborn
, check βbokeh
, check β- and many more!
There are several Docker images (open source) pre-built with the most popular libraries for Data Science, ML and Deep Learning:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
# Data for plotting
t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2 * np.pi * t)
fig, ax = plt.subplots()
ax.plot(t, s)
ax.set(xlabel='time (s)', ylabel='voltage (mV)',
title='About as simple as it gets, folks')
ax.grid()
fig.savefig("test.png")
plt.show()
Install your own librariesΒΆ
Did we miss any library that you need? Just install it! This environment is completely isolated and you can install your own stuff. You can also include custom requirements.txt
that will be installed automatically.
!pip install maya
import maya
tomorrow = maya.when('tomorrow')
tomorrow.slang_date()
tomorrow.slang_time()
Upload or download filesΒΆ
You might have noticed that our voltage chart, we saved the figure as test.png
, you can download it just by right clicking on it on the tree viewer on the left (not available on mobile, where a regular Notebook is loaded).
Great for EducationΒΆ
We created Notebooks AI for our own students, so Education is 1st class citizen. We've included multiple solutions to simplify your life as a teacher. For example, a public view of your project where a student can just fork and start working immediately.
We've also created our own extensions for JupyterLab, like JupyterLab Solutions. As a teacher, you can hide solutions for your students:
Write a function add
that receives 2 numbers and returns the sum of them:
def add(x, y):
return x + y
Need help, have questions?ΒΆ
We're here to help :) Just open an issue here: https://github.com/notebooks-ai/notebooks-help/issues