Jupyter has revolutionized data science, and it started with a chance meeting between two students on March 8, 2021, 12:00 PM PST Commentary: Jupyter makes it easy for data scientists to collaborate, and the open source project s history reflects this kind of communal effort. Image: iStockphoto/shironosov
If you want to do data science, you re going to have to become familiar with Jupyter. It s a hugely popular open source project that is best known for Jupyter Notebooks, a web application that allows data scientists to create and share documents that contain live code, equations, visualizations and narrative text. This proves to be a great way to extract data with code and collaborate with other data scientists, and has seen Jupyter boom from roughly 200,000 Notebooks in use in 2015 to millions today.
Immerse yourself in learning Python and introductory data analytics with this bookâs project-based approach. Through the structure of a ten-week coding bootcamp course, youâll learn key concepts and gain hands-on experience through weekly projects.
Each chapter in this book is presented as a full week of topics, with Monday through Thursday covering specific concepts, leading up to Friday, when you are challenged to create a project using the skills learned throughout the week. Topics include Python basics and essential intermediate concepts such as list comprehension, generators and iterators, understanding algorithmic complexity, and data analysis with pandas. From beginning to end, this book builds up your abilities through exercises and challenges, culminating in your solid understanding of Python.Challenge yourself with the intensity of a coding bootcamp experience or learn at your own pace. With this hands-on learning approach, you will gain the skills you need to ju
Strangeworks Launches Quantum Ecosystem to Humanize Quantum Technologies
Quantum ecosystem and European expansion underscores firm s commitment to globalize, democratize and streamline quantum computing
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AUSTIN, Texas, Feb. 16, 2021 /PRNewswire/ Strangeworks, Inc., a quantum computing software company dedicated to making quantum computing accessible, today announced three key initiatives as part of its mission to foster a global quantum workforce, humanize access to quantum computing and streamline existing quantum production workflows. Combined, these offerings establish Strangeworks as the leading Quantum Service Provider™ providing scientists, researchers, software developers, and enthusiasts with a complete quantum ecosystem that includes a browser-based development environment, hardware, software, educational resources, and an ever-growing library of quantum code to start from:
This will create a conda environment named
darn with the latest Python 3 package ready to go. You should be presented with a list of packages that will be installed and asked if you wish to proceed. To do so, just enter the character
y. If this operation is successful, you should see the following output at the end:
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate darn
#
# To deactivate an active environment, use
#
# $ conda deactivate
As the message suggests, you will need to type the following command to activate and start entering commands within our environment named
bazel test command. For example,
bazel test tf quant finance/math/random ops/sobol:sobol test
will run tests in
sobol test.py
.
Tests run using Python version 3. Please make sure that you can
run
import tensorflow in the Python 3 shell. Otherwise, tests might fail.
Building a custom pip package
The following commands will build custom pip package from source and install it:
# sudo apt-get install bazel git python python-pip rsync # For Ubuntu.
git clone https://github.com/google/tf-quant-finance.git
cd tf-quant-finance
bazel build :build pip pkg
./bazel-bin/build pip pkg artifacts
pip install user upgrade artifacts/ .whl
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