Analytics Vidhya

OCTOBER 27, 2019

Overview Big Data is becoming bigger by the day, and at an unprecedented pace How do you store, process and use this amount of. The post PySpark for Beginners – Take your First Steps into Big Data Analytics (with Code) appeared first on Analytics Vidhya.

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Big Data Analytics Big Data Analytics Big Data Big Data 283

KDnuggets

OCTOBER 30, 2019

Here are five statistical fallacies — data traps — which data scientists should be aware of and definitely avoid.

Data Scientist 277

Data Scientist 277

Dataconomy

OCTOBER 30, 2019

Aleksandar Kova?evi?, Sales Engineer at InterSystems, shares how companies use MLOps combined with a central multi-model database to get the most out of their machine learning initiatives. Artificial Intelligence (AI) and Machine Learning (ML) are hot topics at the moment. But when it comes to producing quantifiable results, there is. The post MLOps can help overcome risk in AI and ML projects appeared first on Dataconomy.

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ML ML Machine Learning Machine Learning 183

Data Science 101

OCTOBER 31, 2019

Today we are generating data more than ever before. Over the last two years, 90 percent of the data in the world was generated. This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD).

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Data Mining Data Mining Data Mining Data Science 77

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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

Analytics Vidhya

OCTOBER 30, 2019

Overview Gaussian Mixture Models are a powerful clustering algorithm Understand how Gaussian Mixture Models work and how to implement them in Python We’ll also. The post Build Better and Accurate Clusters with Gaussian Mixture Models appeared first on Analytics Vidhya.

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Clustering Python Algorithm Analytics 265

KDnuggets

NOVEMBER 1, 2019

As a developer who is excited about leveraging machine learning for faster and more effective development, these software tools are worth trying out.

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Machine Learning Machine Learning 221

Smart Data Collective

OCTOBER 30, 2019

Machine learning is changing the future of marketing in many beneficial ways. The Digital Marketing Institute reports that 97% of decision makers believe it is the future of marketing. There are a number of tactics that marketers can pursue to optimize campaigns with machine learning algorithms. However, some of these strategies are more limited then marketers would like to think.

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Machine Learning Machine Learning Algorithm Big Data 72

Analytics Vidhya

OCTOBER 29, 2019

Do you want to build your own smart city? Picture it – self-driving cars strolling around, traffic lights optimised to maintain a smooth flow, The post Here are 8 Powerful Sessions to Learn the Latest Computer Vision Techniques appeared first on Analytics Vidhya.

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Analytics Analytics Deep Learning Deep Learning 250

KDnuggets

OCTOBER 31, 2019

A hands on guide to Logistic Regression for aspiring data scientist and machine learning engineer.

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Data Scientist Machine Learning Machine Learning Python 270

DataRobot

NOVEMBER 1, 2019

There is a saying, “Be careful what you wish for; you might just receive it.” One of the first-ever stories to exemplify this saying comes from Greek mythology. The story goes that Midas earned the favor of Silenus, a satyr. Silenus offered Midas a wish, and Midas wished that everything he touched would turn to gold. Immediately, Midas put the power to the test, touching a rose and turning it into solid gold.

Data Science 14

Data Science AI AI 14

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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

Smart Data Collective

NOVEMBER 1, 2019

Machine learning is offering businesses a new opportunity to translate documents. They can use machine learning to translate marketing materials and other literature. However, these AI solutions may not always be the best. Brief Overview of Neural Machine Learning. Towards Data Science has discussed this development. The term is called neural machine translation.

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Machine Learning Machine Learning Data Science AI 66

KDnuggets

OCTOBER 28, 2019

Learn how Bayes Theorem is in Machine Learning for classification and regression!

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Machine Learning Machine Learning 285

KDnuggets

NOVEMBER 1, 2019

This article focused on building an Artificial Neural Network using the Numpy Python library.

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Python 236

KDnuggets

OCTOBER 28, 2019

Data collection is one of the first steps of the data lifecycle — you need to get all the data you require in the first place. To collect the right data, you need to know where to find it and determine the effort involved in collecting it. This article answers the most basic question: where does all the data you need (or might need) come from?

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Data Science 163

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.

KDnuggets

OCTOBER 30, 2019

The problem with RNNs and CNNs is that they aren’t able to keep up with context and content when sentences are too long. This limitation has been solved by paying attention to the word that is currently being operated on. This guide will focus on how this problem can be addressed by Transformers with the help of deep learning.

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Deep Learning Deep Learning 139

KDnuggets

NOVEMBER 1, 2019

This live webinar, Nov 14 @ 12pm EST, on MLOps for production-level machine learning, will detail MLOps, a compound of “machine learning” and “operations”, a practice for collaboration and communication between data scientists and operations professionals to help manage the production machine learning lifecycle. Register now.

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Machine Learning Machine Learning Data Scientist 139

KDnuggets

OCTOBER 29, 2019

Developing an excellent machine learning model is one thing. Deploying it to production is another. Consider these lessons learned and recommendations for approaching this important challenge to help ensure value from your AI work.

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Machine Learning Machine Learning AI AI 138

KDnuggets

OCTOBER 31, 2019

Learn how to approach the challenges when merging an agile methodology into a data science team to bring out the best value your Big Data products.

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Big Data Big Data Big Data Analytics Big Data Analytics 149

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

KDnuggets

OCTOBER 31, 2019

AI-based models are highly dependent on accurate, clean, well-labeled, and prepared data in order to produce the desired output and cognition. These models are fed with bulky datasets covering an array of probabilities and computations to make its functioning as smart and gifted as human intelligence.

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AI AI Data Preparation 129

KDnuggets

OCTOBER 28, 2019

Also: Introduction to Natural Language Processing (NLP); Anomaly Detection, A Key Task for AI and Machine Learning, Explained; How to Become a (Good) Data Scientist — Beginner Guide.

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Data Scientist Natural Language Processing Machine Learning Machine Learning 122

KDnuggets

OCTOBER 28, 2019

Visualizing the datasets is an essential component to identify potential sources of bias and unfairness. DeepMind relied on a method called Causal Bayesian networks (CBNs) to represent and estimate unfairness in a dataset.

Machine Learning 119

Machine Learning Machine Learning 119

KDnuggets

NOVEMBER 1, 2019

Not only can MLonCode help companies streamline their codebase and software delivery processes, but it also helps organizations better understand and manage their engineering talents.

Machine Learning 119

Machine Learning Machine Learning 119

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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

OCTOBER 30, 2019

While AutoML started out as an automation approach to develop optimal machine learning pipelines, extensions of AutoML to Data Science embedded products can now enable the processing of much more, including temporal relational data.

Machine Learning 118

Machine Learning Machine Learning Data Science 118

KDnuggets

OCTOBER 30, 2019

This week in KDnuggets: Feature Selection: Beyond feature importance?; Time Series Analysis: A Simple Example with KNIME and Spark; 5 Advanced Features of Pandas and How to Use Them; How to Measure Foot Traffic Using Data Analytics; Introduction to Natural Language Processing (NLP); and much, much more!

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Natural Language Processing Analytics Analytics Python 116

KDnuggets

OCTOBER 30, 2019

Also: Highest paid positions in 2019 are DevOps, Data Scientist, Data Engineer (all over $100K) - Stack Overflow Salary Calculator, Updated; A neural net solves the three-body problem 100 million times faster; The Last SQL Guide for Data Analysis You’ll Ever Need; How YouTube is Recommending Your Next Video.

Machine Learning 115

Machine Learning Machine Learning Data Scientist SQL 115

KDnuggets

OCTOBER 28, 2019

DataTech is a one-day conference on 16 Mar 2020, at the Technology and Innovation Centre in Glasgow, focusing on key topics in data science, and welcoming members of industry, academia, and the public sector alike. DataTech provides a forum for these different communities to meet, share knowledge and expertise, and forge new collaborations. We are currently welcoming workshop, talk and poster proposals for the DataTech20 conference.

Data Science 115

Data Science 115

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

OCTOBER 31, 2019

These results will go into each each region and employment type to find out the differences and similarities especially between people from Industry and Students.

Data Science 116

Data Science Data Visualization Deep Learning Deep Learning 116

KDnuggets

OCTOBER 29, 2019

Google claimed quantum supremacy, IBM challenged it… but the development is really important for the future of AI.

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Artificial Intelligence Artificial Intelligence AI AI 140

KDnuggets

OCTOBER 29, 2019

In this post, learn how to extend Scikit-learn code to make your experiments easier to maintain and reproduce.

Machine Learning 130

Machine Learning Machine Learning Python 130

Smart Data Collective

OCTOBER 28, 2019

Big data has given birth to a number of new applications. Both mobile and desktop devices are able to use more sophisticated applications to serve users in every part of the world. Tech Beacon wrote some very insightful guidelines for people trying to develop applications. Big data isn’t just useful for developing new applications. It also is ideal for monitoring these applications more easily.

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Big Data Big Data Hadoop Data Mining 59

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.