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 284

KDnuggets

OCTOBER 30, 2019

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

Data Scientist 270

Data Scientist 270

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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Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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 Algorithm Python Analytics 268

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 234

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 73

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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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 261

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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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

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 69

KDnuggets

OCTOBER 28, 2019

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

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Machine Learning Machine Learning 276

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?

Data Science 184

Data Science 184

KDnuggets

NOVEMBER 1, 2019

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

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Python 231

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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 156

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 153

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 170

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 142

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

Business Intelligence

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 139

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.

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Machine Learning Machine Learning 123

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.

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Machine Learning Machine Learning Data Science 122

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 120

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Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

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 117

Machine Learning Machine Learning 117

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 115

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.

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Machine Learning Machine Learning Data Scientist SQL 114

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.

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Data Science 114

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

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.

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Data Science Data Visualization Deep Learning Deep Learning 115

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 151

KDnuggets

OCTOBER 29, 2019

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

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Machine Learning Machine Learning Python 139

Smart Data Collective

OCTOBER 30, 2019

Many of our colleagues have written extensively about the impact big data is having on the gaming industry. They have said that big data technology is probably the biggest game changer in the industry. Kevin Rands of CIO is one of the experts to discuss the state of big data in the gaming industry. He said big data analysis gives companies a long-term strategy that helps them gain the strongest competitive edge.

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Big Data Big Data Machine Learning Machine Learning 66

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

AI