AI News, PyCon Montreal 2015 tutorials – Hands-on way to learn Data Science in Python

PyCon Montreal 2015 tutorials – Hands-on way to learn Data Science in Python

PyCon(s) carry a benevolent motive of helping the Python community worldwide by providing extensive knowledge resources. I started following PyCon conferences from 2013.

workshops inspired me to follow it back in the year 2014 and this craze continued in 2015 as well.

Workshops aim to provide 3 hour hands on sessions where the instructor also acts as a facilitator.

We recommend beginners to watch these videos in the listed sequence to help understand these concepts better, intermediates &

personally use IPython notebooks for the interactive data exploration and recommend it to every data science professional.

It provides a super basic introduction of notebooks in Python, which then moves on to the explanation of super developed notebooks for Python such as iPython and Jupyter.

This videos demonstrates the methods to make statistical inferences in Python by evaluating the sample, quantifying precision, hypothesis testing and performing similar steps.

This workshop beautifully explains the concept of data visualization supported by various other features (matplotlib) of python which are used to make your visualizations more apt and appealing. It also feature sets of challenges which will definitely excite your grey cells.

This workshop begins with deriving Bayes theorem, then proceeds to the Bayesian statistics followed by solving some real world cases.

It begins with explaining machine learning with scikit-learn, then explains the concepts of supervised and unsupervised learning and eventually, concludes with model validation.

It further deep dives into the concepts of machine learning, thereby, explaining the concepts such as heterogeneous data modelling, text feature extraction, clustering, large scale text classification for sentimental analysis etc.

Here, the instructors has intended to create a contest similar to Kaggle competition among the attendees by forming their groups and helping them with the required tips, tricks, hacks used to solve such questions.

It also covers various practice problems on pandas, DataFrames, setup evaluation functions, test dummy solutions etc.

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