You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Downloads for my O'Reilly Online Learning live training course Python Data Science Full Throttle: Introductory Artificial Intelligence (AI), Big Data and Cloud Case Studies
Setting Up a Custom Conda Environment
These are the commands I used to set up a fresh environment. They create a custom environment named pydsft — you can choose any name you like:
Create the custom environment
conda create --name pydsft
Activate the environment you just created
conda activate pydsft
The following two commands install most of what you need for the content from ch11, ch12, ch13, ch14, ch15 and a good chunk of ch16—if you’re working from our books or videos, you might need to subsequently install a few other packages. NOTE: You might want to install one package at a time from the following command as it can take a significant amount of time to resolve all the interdependencies if you do it all at once.
The pip command is needed because a few packages are not available through the conda repository. If any package install fails with conda on Windows, use pip to install it.
Past Course Links (accessible only if you were registered for that course)
The authors and publisher of this book have used their best efforts in preparing this book. These efforts include the development, research, and testing of the theories and programs to determine their effectiveness. The authors and publisher make no warranty of any kind, expressed or implied, with regard to these programs or to the documentation contained in this book. The authors and publisher shall not be liable in any event for incidental or consequential damages in connection with, or arising out of, the furnishing, performance, or use of these programs.
About
Downloads for my Safari Online Learning live training course Python Data Science Full Throttle: Introductory Artificial Intelligence (AI), Big Data and Cloud Case Studies