No matter how good you are in programming with respect to a language like python you may not be able to remember all the functions names or syntax or function parameters. So you may require to use intellisense or autocomplete feature of Jupyter notebook while programming in pandas, python and similar libraries.
In the below video, Jupyter Notebook Autocomplete Intellisense and Menu Shortcuts is discussed.
Yes it is possible to use intellisense and autocomplete in Jupyter Notebook.
As you can see in above image, you just need to press TAB key after typing the dot after np and you will get all the functions realted to numpy.
Similarly if you want to see the parameters or signature of a function, type the function name and then the opening bracket of the function and then press Shift+Tab as shown below.
You may like to read our other popular posts as below:
- Linear Regression in Python in 10 Lines
- Logistic Regression In Python in 10 Lines
- Generating Synthetic Data for Logistic Regression
- Scatter Plot using Seaborn and Sklearn
I hope you enjoyed this article and can start using some of the techniques described here in your own projects soon.
Do you really think that a neural network is a block box? I believe, a neuron inside the human brain may be very complex, but a neuron in a neural network is certainly not that complex. In this video, we are going to discuss how to implement a neural network from scratch in Python.
How to Implement Linear Regression From Scratch in Python
What disadvantage you will found using auto competition and what changes you suggest to the jupyter notebook