- Jupyter
- Integrated development environment (IDE) where you type your code https://jupyter.org/
- It lets you execute partial lines of the code which is useful for ML
pip install notebook
- Scikit-learn library
- Provides common algorithms
- Numpy library
- NumPy is an open source mathematical and scientific computing library for Python programming tasks. The name NumPy is shorthand for Numerical Python. The NumPy library offers a collection of high-level mathematical functions including support for multi-dimensional arrays, masked arrays and matrices. - techtarget.com
- Pandas library
- Data analysis which provides a concept called data frame, simliar to an Excel spreadsheet with rows and columns
- MatPlotLib library
- Two dimentional library for creating graphs and plots
- Anaconda
- Distrubtion software that downloads and installs Jupyter and the data science libraries mentioned above https://www.anaconda.com/download/success
- Kaggle.com
- Has data science projects and sample data sets
- Example Video game sales
- Install Anaconda, I still needed to manually install Jupyter and required libraries
--- text classification
pip install notebook pandas sklearn
--- image recognition
pip install tensorflow (this installed keras)
pip install split-folders opencv-python
pip install matplotlib
- Run notebook server, this should open http://localhost:8888/tree as the Jupyter dashboard
jupyter notebook
- Create Jupyter notebook, by default it will open to your users directory, I created the folder
ml-notebooks, from the GUI selectedNew->Python 3 ipykernal - Rename the notebook from
Untitledto be something related to your model, as always naming things is hard so I usedHelloWorldlike Mosh's example :D
Command mode (press ESC to enable)
b, insert new cell belowa, insert a new cell aboved d, delete cellSHIFT TABon a method to show its tooltipCTRL ENTERwith cell active, runs just that cell and doesnt add a new cell below