KDnuggets

NOVEMBER 22, 2019

To demonstrate the implementation complexity differences along the AutoML highway, let's have a look at how 3 specific software projects approach the implementation of just such an AutoML "solution," namely Keras Tuner, AutoKeras, and automl-gs.

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Machine Learning Machine Learning Python 290

Analytics Vidhya

NOVEMBER 18, 2019

Overview Here’s a quick introduction to building machine learning pipelines using PySpark The ability to build these machine learning pipelines is a must-have skill. The post Want to Build Machine Learning Pipelines? A Quick Introduction using PySpark appeared first on Analytics Vidhya.

Machine Learning 285

Machine Learning Machine Learning Analytics Analytics 285

Dataconomy

NOVEMBER 21, 2019

The era of everything-as-a-service (XaaS) has provided both an opportunity and a challenge for companies across industries. The XaaS model, a subscription-based solution that makes cloud-based applications available on demand unlike the traditional license-based platforms of the past, delivers several noteworthy advantages over its predecessors. Between cost reductions and easier.

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Internet of Things 119

Smart Data Collective

NOVEMBER 21, 2019

Big data is transforming the daily realities of running a business. Companies can use big data to handle certain tasks more quickly and cost-effectively than ever. Vince Campisi, CIO of GE Software, Ash Gupta, an executive with American Express, and many other companies use big data to get a competitive advantage. Of course, big data also raises some new challenges.

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Big Data Big Data Predictive Analytics Analytics 109

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

AI

KDnuggets

NOVEMBER 22, 2019

If you are a new Data Scientists early in your professional journey, and you’re a bit confused and lost, then follow this advice to figure out how to best contribute to your company.

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Data Scientist 273

Analytics Vidhya

NOVEMBER 19, 2019

Overview The attention mechanism has changed the way we work with deep learning algorithms Fields like Natural Language Processing (NLP) and even Computer Vision. The post A Comprehensive Guide to Attention Mechanism in Deep Learning for Everyone appeared first on Analytics Vidhya.

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Deep Learning Deep Learning Natural Language Processing Algorithm 278

Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. That work is now due for an update. In this post, we present a new version and a demo NER project that we trained to usable accuracy in just a few hours.

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KDnuggets

NOVEMBER 21, 2019

This tutorial will take you through two options that have automated the geocoding process for the user using Python, Selenium and Google Geocoding API.

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Python 287

DataCentric podcast

NOVEMBER 19, 2019

Arm's Mohamed Awad, as VP in Arm's Infrastructure group, is front-and-center in their architecture's invasion into enterprise compute. Let's look at where ARM stands in the enterprise today: Nearly every tier-1 OEM has an Arm server offering Every major public cloud vendor offers Arm instances NVIDIA, Marvell, Fujitsu, & Ampere jointed announced an Arm-based Super Computer reference platform at SC19 this week As we look forward towards a 5G-enabled edge, Arm is finding itself

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Data Science 101

NOVEMBER 19, 2019

Introduction to Probability by Joseph Blitzstein and Jessica Hwang is available as a free PDF download.

Data Science 89

Data Science 89

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Database

DataRobot

NOVEMBER 22, 2019

The recent uproar surrounding the credit scoring algorithm employed by the Apple Card presents an opportunity to review the manifold types of biases that can affect AI algorithms, the possible consequences of neglecting such biases, and the best practices for allowing companies to develop processes to ensure that AI bias problems are adequately addressed.

AI 11

AI AI Algorithm 11

KDnuggets

NOVEMBER 22, 2019

We will focus here exactly on that part of the analysis that transforms words into numbers and texts into number vectors: text encoding.

Analytics 281

Analytics Analytics 281

DataCentric podcast

NOVEMBER 18, 2019

As Hewlett Packard Enterprise launches its bare-metal container platform at KubeCon this week, Moor Insights & Strategy analysts Matt Kimball and Steve McDowell have a conversation with HPE VP and Chief Cloud Strategist Robert Christiansen. The guys talk about how HPE views cloud workloads, and how the power of Kubernetes and containers might just be the right answer for both cloud and edge.

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Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. That work is now due for an update. In this post, we present a new version of the library, new vectors, new evaluation recipes, and a demo NER project that we trained to usable accuracy in just a few hours.

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Natural Language Processing Data Scientist Machine Learning Machine Learning 52

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

DataRobot

NOVEMBER 21, 2019

In all segments of commercial banking competition is more intense and top line growth harder to achieve than ever before.

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AI AI 15

KDnuggets

NOVEMBER 19, 2019

This post will be dedicated to explaining the maths behind Bayes Theorem, when its application makes sense, and its differences with Maximum Likelihood.

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Data Science 101

NOVEMBER 20, 2019

[ Image source ]. We are living in the data-driven world where every industry be it healthcare, finance, omnichannel retail, agriculture, logistics and much more runs on data. The data is one of the key essentials for increasing revenues and cost savings. Data can be considered as a tool that is banked on by the organizations for making smarter decisions and it is necessary to survive in these competitive markets.

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Big Data Big Data Database Data Science 103

Smart Data Collective

NOVEMBER 22, 2019

Big data is transforming many facets of our lives. One of the ways consumers are looking to big data is with the student loan crisis. Big data advances could also make the government more understanding with its student loan forgiveness program. Big Data Could Turn the Student Loan Crisis on its Head. There are multiple applications of big data for solving the student loan crisis.

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Big Data Big Data 98

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science

DataRobot

NOVEMBER 20, 2019

The National Association of REALTORS® is America’s largest trade association, representing over 1.4 million members around the country. Members include brokers, salespeople, property managers, counselors, and others engaged in all aspects of the real estate industry. With such a large membership to serve, it’s important that the association deliver value and serve its members by making more optimal decisions.

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AI AI 9

KDnuggets

NOVEMBER 21, 2019

This blog shows how text data representations can be used to build a classifier to predict a developer’s deep learning framework of choice based on the code that they wrote, via examples of TensorFlow and PyTorch projects.

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Deep Learning Deep Learning Data Preparation 236

Shreyansh Singh

NOVEMBER 19, 2019

A bit late for writeups, but still here are the solutions to the challenges I solved during the CTF. The CTF was from 15 Nov. 2019, 22:30 IST — Mon, 18 Nov. 2019, 10:30 IST. It was a decent CTF with quality challenges, from both beginner to advanced level. Update : The scripts to solve and the flags are present in this repo. I’ll do the writeups category-wise - Crypto pre-legend — 100 pts 9EEADi^⁸:E9F3]4@>⁴=2J32==^D@>6E9:?

Database 52

Database Python 52

Data Science 101

NOVEMBER 22, 2019

Here are this week’s news and announcements related to Cloud Data Science. Plus, there are some links for Videos and Tutorials. Announcements. Google Introduces Explainable AI Many industries require a level of interpretability for their machine learning models. Black box solutions are not always ok. Google is launching Explainable AI which quantifies the impact of the various factors of the data as well as the existing limitations.

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Cloud Data Data Science Azure AWS 99

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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

Analytics

KDnuggets

NOVEMBER 21, 2019

This article aims to explain why this drive towards the use of notebooks in production is an anti pattern, giving some suggestions along the way.

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Python 247

KDnuggets

NOVEMBER 21, 2019

Autoencoders can be a very powerful tool for leveraging unlabeled data to solve a variety of problem, such as learning a "feature extractor" that helps build powerful classifiers, finding anomalies, or doing a Missing Value Imputation.

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Machine Learning Machine Learning 214

KDnuggets

NOVEMBER 18, 2019

When training a neural network in deep learning, its performance on processing new data is key. Improving the model's ability to generalize relies on preventing overfitting using these important methods.

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Deep Learning Deep Learning 213

KDnuggets

NOVEMBER 21, 2019

Also: Bring the scientific rigor of reproducibility to your Data Science projects; Neutrinos Lead to Unexpected Discovery in Basic Math ; The media gets really excited about AI. Maybe a bit too excited.

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Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

Analytics

KDnuggets

NOVEMBER 20, 2019

Your spectacularly-performing machine learning model could be subject to the common culprits of class imbalance and missing labels. Learn how to handle these challenges with techniques that remain open areas of new research for addressing real-world machine learning problems.

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Machine Learning Machine Learning Data Preparation 183

KDnuggets

NOVEMBER 19, 2019

As cornerstones of scientific processes, reproducibility and replicability ensure results can be verified and trusted. These two concepts are also crucial in data science, and as a data scientist, you must follow the same rigor and standards in your projects.

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Data Science Data Scientist 177

KDnuggets

NOVEMBER 19, 2019

In this article, we are going to talk about popular languages for Data Science and briefly describe each of them.

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Data Science Python 227

KDnuggets

NOVEMBER 21, 2019

Brush up on your Python basics with this post on creating, using, and manipulating tuples.

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Python 232

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.