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| 4. NumPy Basics - IPython Notebook Tutorial |
Title : 4. NumPy Basics - IPython Notebook Tutorial
Duration : 30:43
Channel : Roshan
Label : Machine Learning (Field Of Study), Python (Software), Research (Industry), numpy, scipy, Amazon Web Services (Website), Artificial Intelligence (Industry), Roshan, Roshan Rush, Tutorial, IPython, Python (Programming Language), Mathematics (Field Of Study), Statistics (Field Of Study), Scientific Computing, Research And Development (Industry), IPython Notebook
Duration : 30:43
Channel : Roshan
Label : Machine Learning (Field Of Study), Python (Software), Research (Industry), numpy, scipy, Amazon Web Services (Website), Artificial Intelligence (Industry), Roshan, Roshan Rush, Tutorial, IPython, Python (Programming Language), Mathematics (Field Of Study), Statistics (Field Of Study), Scientific Computing, Research And Development (Industry), IPython Notebook
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| 4. NumPy Basics - IPython Notebook Tutorial |
NumPy tutorial using IPython Notebook development environment. We compare performance of ndarray vs python list performance and basic mathematical operations. We cover most common functions and indexing & slicing. IPython magic used is %timeit, %%timeit and %%capture. We covered the most common functions of NumPy which are: **List Creation** - np.arange() - np.array() - np.zeros() - np.random.random() - np.linspace() **Statistical analysis** - np,max() - np.min() - np.mean() - np.median() - np.std() **Reshaping** - np.reshape() - np.ravel() This is open source, Github/NBViwer: http://nbviewer.ipython.org/github/twistedhardware/mltutorial/blob/master/notebooks/IPython-Tutorial/4%20-%20Numpy%20Basics.ipynb