Analytics Vidhya
FEBRUARY 10, 2022
This article was published as a part of the Data Science Blogathon. Introduction Model Development is a critical stage in the life cycle of a Data Science project. We attempt to train our data set using various forms of Machine Learning models, either supervised or unsupervised, depending on the Business Problem. Given many models available for […].
KDnuggets
FEBRUARY 10, 2022
There is a difference in the level of experience compared to Junior, Mid-Level, and Senior Data Scientists. This article will go through the expectations for all job roles and what is required to move up the ladder.
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Analytics Vidhya
FEBRUARY 10, 2022
This article was published as a part of the Data Science Blogathon. This is the 2nd blog of the MLOps series. Introduction This article is part of an ongoing blog series on Machine Learning Operations(MLOps). In the previous article, we have gone through the introduction of MLOps. We have seen differences in traditional software development in […].
Smart Data Collective
FEBRUARY 10, 2022
We have witnessed some horrifying data breaches over the last year. One of the worst was when a team of Chinese hackers penetrated the security of the Microsoft Exchange and accessed the accounts of over 250,000 global organizations. The Colonial Pipeline and SolarWinds were also victims to hackers. While large corporations like these will continue to be targets for data breaches, small businesses are also at risk.
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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.
Analytics Vidhya
FEBRUARY 10, 2022
This article was published as a part of the Data Science Blogathon. Objective “True optimization is the revolutionary contribution of modern research to decision processes” – George Dantzig. This article discusses solving a resource allocation problem using linear programming in Python. We will find an optimal value for a linear equation with different linear constraints.
DataKitchen
FEBRUARY 10, 2022
The post Building the Business Case for DataOps first appeared on DataKitchen.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
KDnuggets
FEBRUARY 10, 2022
This article is an excerpt from the book Machine Learning with PyTorch and Scikit-Learn is the new book from the widely acclaimed and bestselling Python Machine Learning series, fully updated and expanded to cover PyTorch, transformers, graph neural networks, and best practices.
Analytics Vidhya
FEBRUARY 10, 2022
This article was published as a part of the Data Science Blogathon. Overview In this article, we will be closely working with the heart disease prediction and for that, we will be looking into the heart disease dataset from that dataset we will derive various insights that help us know the weightage of each feature and […]. The post Heart Disease Prediction using Machine Learning appeared first on Analytics Vidhya.
KDnuggets
FEBRUARY 10, 2022
Read this collection of humorous, insightful quotes around data science that will hopefully brighten your day and make you laugh!
Analytics Vidhya
FEBRUARY 10, 2022
This article was published as a part of the Data Science Blogathon. Introduction Phonepe, Google Pay (Tez) are ubiquitous names in the Indian payment ecosystem and the top two players in the area. According to Phonepe pulse report, it has133 million monthly active users as of July’21. For the Q3-21 quarter, the total transactions were 526.8 Cr […].
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
FEBRUARY 10, 2022
Going forward, data professionals have found a new way to address the scalability of sources through data mesh.
Edwin Chen
FEBRUARY 10, 2022
I built a visualization to explore embeddings a few years ago, but never posted it more broadly. So here it is! [link]. These are GloVe embeddings projected into 2D, colorized via k-means in the original space. You can see, for example, that the cluster in pink ….
IBM Big Data Hub
FEBRUARY 10, 2022
As a data scientist for IBM Consulting, I’ve been fortunate enough to work on several projects to fulfill the various needs of IBM clients. Over my time at IBM, I have seen technology applied to various use cases that I would have never originally considered possible, which is why I was thrilled to steward the implementation of artificial intelligence to address one of the most insidious societal issues we face today, racial injustice.
Cloudera
FEBRUARY 10, 2022
After the launch of Cloudera DataFlow for the Public Cloud (CDF-PC) on AWS a few months ago, we are thrilled to announce that CDF-PC is now generally available on Microsoft Azure, allowing NiFi users on Azure to run their data flows in a cloud-native runtime. . With CDF-PC, NiFi users can import their existing data flows into a central catalog from where they can be deployed to a Kubernetes based runtime through a simple flow deployment wizard or with a single CLI command.
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.
Smart Data Collective
FEBRUARY 10, 2022
Cloud technology has completely transformed the ways that we access online content. A variety of streaming services use the cloud to connect users with the content they are looking for. Dacast has a post on the 15 best cloud streaming services. Many businesses are leveraging these solutions to provide content to their viewers, since 94% of them have discovered that it is the best way to grow their brands.
Jedox
FEBRUARY 10, 2022
What is business partnering and why is it becoming increasingly important for finance professionals to engage with the topic? Learn from finance expert Anders Liu-Lindberg how you can use insights from the finance department to strengthen collaboration in your company. How do you see the role of Finance in the company? Compliance and control-oriented ensuring that the house in order or business advisors that drive value creation and help unleash the potential of the company’s strategy?
Smart Data Collective
FEBRUARY 10, 2022
Cybersecurity is a growing concern. In 2018 alone, over 1,200 data breaches were orchestrated and nearly 450 million records were compromised. There will be more pressure to improve cybersecurity as these threats escalate. We have a problem with data security. We are more than 70 years into the digital age. We have found that data is one of the most important assets a person or company can have, and the threats of destruction and theft are constantly looming.
David Menninger's Analyst Perspectives
FEBRUARY 10, 2022
Organizations of all sizes are dealing with exponentially increasing data volume and data sources, which creates challenges such as siloed information, increased technical complexities across various systems and slow reporting of important business metrics. Migrating to the cloud does not solve the problems associated with performing analytics and business intelligence on data stored in disparate systems.
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.
Alation
FEBRUARY 10, 2022
Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Let’s discuss what data classification is, the processes for classifying data, data types, and the steps to follow for data classification: What is Data Classification?
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