pandas dataframes

Pandas Indexing Examples: Accessing and Setting Values on DataFrames

21 Aug 2019   Some common ways to access rows in a pandas dataframe, includes label-based (loc) and position-based (iloc) accessing.

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spark scala

Spark Dataframe Examples: Pivot and Unpivot Data

10 Aug 2019   Pivoting and unpivoting are very commonly-used data transformation operations. Use them when you want to switch from a row-based to a column-based view and vice-versa.

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jupyter-notebooks scala spark

Jupyter Notebook Kernels: How to Add, Change, Remove

28 Jul 2019   Add, remove and change Kernels to use with Jupyter notebook

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paper-summary sequence-learning

Paper Summary: Sequence to Sequence Learning with Neural Networks

14 Jul 2019   Summary of the 2014 article "Sequence to Sequence Learning with Neural Networks" by Sutskever et al.

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Paper Summary: A New Probabilistic Model for Title Generation

30 Jun 2019   Summary of the 2002 article "A New Probabilistic Model for Title Generation" by Jin and Hauptmann.

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paper-summary surveys

Paper Summary: Text Summarization Techniques: A Brief Survey

29 Jun 2019   Summary of the 2017 article "Text Summarization Techniques: A Brief Survey" by Allahyari et al.

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scikit-learn svm

Choosing C Hyperparameter for SVM Classifiers: Examples with Scikit-Learn

20 Jun 2019   Analysis of the effect of the C parameter on learning SVM models under a noisy data regime. With examples using the Python Library Scikit-learn.

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Michelangelo Palette Overview

08 Jun 2019   Overview of Palette, the feature store system that is part of Uber's Michelangelo Mahcine Learning Platform. Based off the talk given at qcon.ai.

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paper-summary embeddings surveys

Paper Summary: From Word to Sense Embeddings: A Survey on Vector Representations of Meaning

02 Jun 2019   Summary of the 2018 article "From Word to Sense Embeddings: A Survey on Vector Representations of Meaning" by Camacho-Collados and Pilehvar.

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projects data-science project-work

Helping Data Science Projects Succeed: 5 Tips on how to Avoid Becoming a Statistic

01 Jun 2019   5 real-world tips to help you avoid failures in data science projects. Suitable for both practitioners and project leads.

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