Domino Data Lab

JANUARY 6, 2019

Lately I’ve been developing curriculum for a client for their new “Intro to Data Science” sequence of courses. Educational materials are available online for their Data 8 foundations course and their Data 100 intermediate course, as well as their textbook, Inferential and Computational Thinking. Introduction.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

CDW Research Hub

JULY 31, 2019

While we’re still in the early days of the design and development of intelligent conversational AI, Google quite rightly announced that we were moving from a mobile-first to an AI- first world, where we expect technology to be naturally conversational, thoughtfully contextual, and evolutionarily competent. Note that you need python 3.6.x

Deep Learning 49

Deep Learning Machine Learning Testing Modeling 49

Sisense

AUGUST 6, 2020

Developing analytic apps is a bold new direction for product teams. The Toolbox is where we talk development best practices, tips, tricks, and success stories to help you build the future of analytics and empower your users with the insights and actions they need. It is a powerful query language and yet the syntax is quite simple.

Software 52

Software Data Processing Consulting Testing 52

Domino Data Lab

JULY 2, 2019

Then click the Synthesize button in AutoPandas to get back a snippet of code in Python. The authors of AutoPandas observed that: The APIs for popular data science packages tend to have relatively steep learning curves. You can provide “before” and “after” versions of a DataFrame to AutoPandas as an input-output example pair.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Domino Data Lab

DECEMBER 2, 2020

Use the denpro R package. Before we can discuss density-based clustering, we first need to cover a topic that you may have seen in a topology course: ?-neighborhoods. The Level Set Tree clustering algorithm was developed in 2010 by Chaudhuri and Dasgupta, two computer scientist at UC San Diego. Preliminary: ?-Balls Application.

Metrics 116

Metrics KDD Testing Machine Learning 116

The Unofficial Google Data Science Blog

MARCH 13, 2017

Of course, there is benefit to an improved understanding of deep networks beyond the satisfaction of curiosity — developers can use this to debug and improve models; end-users can understand the cause of a model’s prediction, and develop trust in the model. Of course, our problem formulation has limitations.

IT 68

IT Visualization Modeling Uncertainty 68

Domino Data Lab

AUGUST 22, 2019

Data scientists and researchers require an extensive array of techniques, packages, and tools to accelerate core work flow tasks including prepping, processing, and analyzing data. Most of these dependencies are from nltk (the Natural Language Toolkit) and gensim (another natural language library for Python). nltk.download('punkt').

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

O'Reilly on Data

DECEMBER 9, 2019

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. CI theory was developed around 1937 by Jerzy Neyman, a mathematician and one of the principal architects of modern statistics.

Statistics 27

Statistics Uncertainty Risk Marketing 27

O'Reilly on Data

JANUARY 25, 2021

We’ve explored usage across all publishing partners and learning modes, from live training courses and online events to interactive functionality provided by Katacoda and Jupyter notebooks. The results are, of course, biased by the makeup of the user population of O’Reilly online learning itself. frameworks.

Machine Learning 363

Machine Learning Software Testing Technology 363

Sisense

MAY 21, 2020

In our Partner Showcase , we highlight the amazing integrations, joint projects, and new functionalities developed with our technology partners at companies like Google and others. Data Freedom is a key focus and by better understanding customer needs, we will create more packaged solutions.”. We’re stronger when we work together.

Digital Transformation 98

Digital Transformation Cost-Benefit Uncertainty Software 98