Peter James Thomas
MARCH 9, 2020
The author, engaged in measuring maturity – © Jennifer Thomas Photography – view full photo. In the thirteen years that have passed since the beginning of 2007, I have helped ten organisations to develop commercially-focused Data Strategies [1]. I last wrote about the process of creating a Data Strategy back in 2014 and – with the many changes that the field has seen since then – am overdue publishing an update, so watch this space.
DataCamp
MARCH 10, 2020
Find out how to build a healthy and sustainable data strategy that will move the needle for your company.
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Andrew White
MARCH 9, 2020
Diane Coyle‘a new paper, The Value of Data , is most interesting. The paper’s findings and recommendations seem somewhat consistent, and are focused on public policy implications for private markets, as is the recent EU Data Strategy white paper. After reading both and comparing the recommendations made to how markets operate and how information drives competitive behaviour, I found questions and challenges in both papers and shared a few of them in a recent blog.
Analytics Vidhya
MARCH 10, 2020
Starting your Deep Learning Career? Deep learning can be a complex and daunting field for newcomers. Concepts like hidden layers, convolutional neural networks, backpropagation. The post Getting into Deep Learning? Here are 5 Things you Should Absolutely Know appeared first on Analytics Vidhya.
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Rocket-Powered Data Science
MARCH 10, 2020
In 2019, I was asked to write the Foreword for the book “ Graph Algorithms: Practical Examples in Apache Spark and Neo4j “ , by Mark Needham and Amy E. Hodler. I wrote an extensive piece on the power of graph databases, linked data, graph algorithms, and various significant graph analytics applications. In their wisdom, the editors of the book decided that I wrote “too much” So, they correctly shortened my contribution by about half in the final published version of my Fo
Corinium
MARCH 11, 2020
With customer expectations rising higher than ever before, it’s never been tougher for organisations to deliver outstanding experiences. To succeed, CCOs need a healthy dose of what Churchill called “corkscrew thinking”. Winston Churchill knew the value of unconventional ideas. He called it “corkscrew thinking”, and it became the secret weapon that saw the Allies through the lowest points of World War Two.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Analytics Vidhya
MARCH 9, 2020
Learn how to build a decision tree model using Weka This tutorial is perfect for newcomers to machine learning and decision trees, and those. The post Build a Decision Tree in Minutes using Weka (No Coding Required!) appeared first on Analytics Vidhya.
Rocket-Powered Data Science
MARCH 10, 2020
50 years after the publication of Alvin Toffler ’s landmark book “ Future Shock “, a new book “ After Shock ” is here. This 540-page compendium collects over 100 modern-day perspectives on After Shock from leading futurists, including deep assessments of Toffler’s formidably prescient predictions from half a century ago, along with a status check on the current exponential growth (“shock”) in all sectors of the world economy, from the unique vantage poin
Corinium
MARCH 9, 2020
The rise of data and analytics in the insurance industry means the underwriting profession is changing fast. Not everyone is thrilled about the rise of AI in the insurance industry.
KDnuggets
MARCH 9, 2020
Upgrading your machine learning, AI, and Data Science skills requires practice. To practice, you need to develop models with a large amount of data. Finding good datasets to work with can be challenging, so this article discusses more than 20 great datasets along with machine learning project ideas for you to tackle today.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
Analytics Vidhya
MARCH 8, 2020
Introduction spaCy is my go-to library for Natural Language Processing (NLP) tasks. I’d venture to say that’s the case for the majority of NLP. The post spaCy Tutorial to Learn and Master Natural Language Processing (NLP) appeared first on Analytics Vidhya.
BA Learnings
MARCH 8, 2020
Most software development and process improvement projects involve introducing new ways of working as part of implementation. Creating a procedure document that users can follow thus becomes a key activity for business analysts that needs to be completed so that system users can perform their duties using the new system or process on day one. So, what exactly is a procedure and how is this different from a process?
Juice Analytics
MARCH 10, 2020
Data storytelling can feel like a misnomer. How can it be storytelling if the story evolves over time or mutates with the interactions of the user? Perhaps we need a new term like story-finding, story-framing , or choose-your-own-adventure. The things we call data stories fall on a spectrum of flexibility, from explanatory to exploratory: A static narrative with a message intended to be consistent across the audience.
KDnuggets
MARCH 11, 2020
Let's talk about covid-19; the reality, the numbers, and the data science.
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The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
Analytics Vidhya
MARCH 13, 2020
Pivot tables – the Swiss Army Knife of data analysis I love how quickly I can analyze data using pivot tables. With one click. The post Here’s How to Build a Pivot Table using Pandas in Python appeared first on Analytics Vidhya.
Data Science 101
MARCH 13, 2020
Elements of Data Science by Allen Downey is a freely available textbook. It consists of Jupyter Notebooks on Google Colab, so you can view and edit code if you want. This could be a great way to begin your data science and programming journey. The post Elements of Data Science – A free Jupyter Notebook Textbook appeared first on Data Science 101.
erwin
MARCH 12, 2020
Almost 70 percent of CEOs say they expect their companies to change their business models in the next three years, and 62 percent report they have management initiatives or transformation programs underway to make their businesses more digital, according to Gartner. Wouldn’t it be advantageous for these organizations to accelerate these digital transformation efforts?
KDnuggets
MARCH 9, 2020
In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science.
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GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
Analytics Vidhya
MARCH 11, 2020
Introduction to Random Forest What’s the first image that comes to your mind when you think about Random Forest? It conjures up images of. The post A Beginner’s Guide to Random Forest Hyperparameter Tuning appeared first on Analytics Vidhya.
Data Science 101
MARCH 9, 2020
Emily Glassberg Sands is the Head of Data Science at Coursera. This is a nice talk about how Coursera uses data science to improve the scale of teaching and learning. This talk was delivered at Women in Data Science 2020. The post Emily Glassberg Sands – How Data Science Can Unlock Teaching & Learning at Scale appeared first on Data Science 101.
Timo Elliott
MARCH 9, 2020
It’s always hard to make the right decisions when the data is uncertain. And that’s currently more important than ever, faced with the rise of the SARS-CoV-2 novel coronavirus and COVID-19, the disease it causes. For example, there are currently many discussions about the “true” mortality rate of the Covid-19 coronavirus. Some people insist that the currently reported mortality rates are wildly overestimated because of the “missing denominator” problem—the abs
KDnuggets
MARCH 13, 2020
This articles outlines 5 sets of tools every lazy full-stack data scientist should use.
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Analytics Vidhya
MARCH 11, 2020
Introduction For loops are the antithesis of efficient programming. They’re still necessary and are the first conditional loops taught to Python beginners but in. The post What are Lambda Functions? A Quick Guide to Lambda Functions in Python appeared first on Analytics Vidhya.
Smart Data Collective
MARCH 13, 2020
It doesn’t matter what the project or desired outcome is, better data science workflows produce superior results. But if you’re still working with outdated methods, you need to look for ways to fully optimize your approach as you move forward. 5 Tips for Better Data Science Workflows. Data science is a complex field that requires experience, skill, patience, and systematic decision-making in order to be successful.
Srividya Sridharan
MARCH 10, 2020
As companies navigate through murky waters amid global health and economic headwinds, as a data and analytics leader, it may feel like there are many things that are out of your hands today. As you weather these conditions, it is still important to chart a steady course and be laser-focused on the parts you can […].
KDnuggets
MARCH 8, 2020
For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.
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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
MARCH 12, 2020
Introduction TensorFlow is a popular and leading open-source framework for developing machine learning and deep learning applications. Developed and pioneered by Google, TensorFlow is. The post Top Highlights from TensorFlow Dev Summit 2020! appeared first on Analytics Vidhya.
Data Science 101
MARCH 7, 2020
Lots of happenings this week. The Cloud Data Science world is keeping busy. Also, the coronavirus is affecting many upcoming conferences, so just be aware of that. News. Honeywell has announced the development of the most powerful quantum computer in the world They are partnering with Microsoft Azure so eventually it will be a part of Azure Quantum Google Cloud Speech to Text got many updates It now supports 7 new languages, has better punctuation, understand whom is speaking, and more Google Cl
Smart Data Collective
MARCH 13, 2020
Big data has opened up a can of worms when it comes to online privacy. A poll cited by Broadband Now shows that 95% of Americans are concerned about their online privacy, but only 50% are taking action to safeguard it. This has opened up discussions about the benefits of online proxies. Concerns about online privacy have peaked this week. A bipartisan bill by Senators Dianne Feinstein and Linsey Graham would require online platforms to make messages unencrypted.
KDnuggets
MARCH 10, 2020
Has coronavirus impacted your conference or other travel plans, and do you anticipate it causing further professional or educational disruption in the near future? Take part in the new KDnuggets poll and have your say.
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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?
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