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Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. As with just about everything in IT, a data strategy must evolve over time to keep pace with evolving technologies, customers, markets, business needs and practices, regulations, and a virtually endless number of other priorities.
If you’ve ever been to London, you are probably familiar with the announcements on the London Underground to “mind the gap” between the trains and the platform. I suggest we also need to mind the gap between data and analytics. These worlds are often disconnected in organizations and, as a result, it limits their effectiveness and agility.
Data mesh planning is a lot like city planning, with both city and data mesh planners aiming to provide as much freedom and flexibility as possible to encourage business growth.
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
This article was published as a part of the Data Science Blogathon. Introduction Flutter where F stands for Front- end, L stands for Language, U stands for UI layout, T stands for Time, T stands for Tools, E stands for Enable, and R stands for Rich. In other words, Flutter is a tool used in […]. The post Building Our Applications Using Flutter appeared first on Analytics Vidhya.
(This is a crosspost from the official Surge AI blog. For background on this blog post. I used to work at Facebook, YouTube, and Twitter. One of the problems I big worked on: what was the right objective function to align our AI systems towards? Optimizing for watch time at ….
(This is a crosspost from the official Surge AI blog. For background on this blog post. I used to work at Facebook, YouTube, and Twitter. One of the problems I big worked on: what was the right objective function to align our AI systems towards? Optimizing for watch time at ….
OCDQ Radio is an audio podcast about data quality and its related disciplines, produced and hosted by Jim Harris. This podcast is no longer an active project, meaning not only do I rarely publish a new episode, but its episodes are only available to listen to on this website and no longer distributed on platforms such as Apple Podcasts and Google Podcasts.
At Dataiku’s Everyday AI Conferences in New York and in Chicago, an important point of discussion was how organizations can make strides towards a reality that encompasses Everyday AI. To achieve this state of AI that’s so ubiquitous that it becomes a part of everyday lives and business, there are of course technical strategy questions to answer. However, the two sessions that we highlight in this blog specifically reveal a potentially less obvious, but nonetheless crucial, element of the journe
This article was published as a part of the Data Science Blogathon. Introduction Streamlit is an open-source tool to build and deploy data applications with less coding compared to other front-end technologies like HTML, CSS, and JavaScript. It is a low-code tool specifically designed for building data science applications. Moreover, the Streamlit library has functions […].
This article was published as a part of the Data Science Blogathon. Introduction The generalization of machine learning models is the ability of a model to classify or forecast new data. When we train a model on a dataset, and the model is provided with new data absent from the trained set, it may perform […]. The post Non-Generalization and Generalization of Machine learning Models appeared first on Analytics Vidhya.
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.
This article was published as a part of the Data Science Blogathon. Introduction With the increasing use of technology, data accumulation is faster than ever due to connected smart devices. These devices continuously collect and transmit data that can be processed, transformed, and stored for later use. This collected data, known as big data, holds valuable […].
This article was published as a part of the Data Science Blogathon. Introduction Which language do we use when it comes to data analysis? Of course, Python, isn’t it? But there is one more language for data analysis which is growing rapidly. Some of you might guess the language – I am talking about Julia. […]. The post An Introduction to Julia for Data Analysis appeared first on Analytics Vidhya.
This article was published as a part of the Data Science Blogathon. Introduction A Merkle tree is a basic component of blockchain technology. It is a mathematical data structure composed of hashes of different data blocks that serve as a summary of all transactions in the block. It also enables efficient and secure verification of […]. The post A Quick Guide to Blockchain: Merkle Tree appeared first on Analytics Vidhya.
This article was published as a part of the Data Science Blogathon. Introduction FaceIO is a cross-browser framework for user facial recognition authentication. Any website can use a JavaScript snippet to implement it. As more and more daily tasks are managed electronically rather than with pen and paper or face-to-face, the demand for quick and […].
Savvy B2B marketers know that a great account-based marketing (ABM) strategy leads to higher ROI and sustainable growth. In this guide, we’ll cover: What makes for a successful ABM strategy? What are the key elements and capabilities of ABM that can make a real difference? How is AI changing workflows and driving functionality? This Martech Intelligence Report on Enterprise Account-Based Marketing examines the state of ABM in 2024 and what to consider when implementing ABM software.
This article was published as a part of the Data Science Blogathon. Introduction Concurrency in DBMS refers to the ability of the system to support multiple transactions concurrently without any data loss or corruption. In a concurrent system, numerous transactions can access and modify the data simultaneously. Each transaction is isolated from other transactions, so […].
This article was published as a part of the Data Science Blogathon. Introduction Biopharmaceutical Industries are the fastest growing industries after considering the basic need for the healthy life of humans and animals. Based on the available literature, the author has identified six major thrust areas of the Biopharmaceutical industry, which has summarized in the […].
This article was published as a part of the Data Science Blogathon. Introduction “Big data in healthcare” refers to much health data collected from many sources, including electronic health records (EHRs), medical imaging, genomic sequencing, wearables, payer records, medical devices, and pharmaceutical research. Its characteristics distinguish it from traditional electronic medical and human health data […].
This article was published as a part of the Data Science Blogathon. Introduction Conventionally, an automatic speech recognition (ASR) system leverages a single statistical language model to rectify ambiguities, regardless of context. However, we can improve the system’s accuracy by leveraging contextual information. Any type of contextual information, like device context, conversational context, and metadata, […].
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.
This article was published as a part of the Data Science Blogathon. Introduction Graph machine learning is quickly gaining attention for its enormous potential and ability to perform extremely well on non-traditional tasks. Active research is being done in this area (being touted by some as a new frontier of machine learning), and open-source libraries […].
This article was published as a part of the Data Science Blogathon. Introduction Cough Audio analysis, one of the breakthroughs of AI in healthcare, often proves valuable in diagnosing respiratory and lung diseases. COVID-19 (Coronavirus Disease 2019) has had devastating effects on humanity, making early detection in patients imperative for its treatment.
This article was published as a part of the Data Science Blogathon. Introduction Hierarchical clustering is one of the most famous clustering techniques used in unsupervised machine learning. K-means and hierarchical clustering are the two most popular and effective clustering algorithms. The working mechanism they apply in the backend allows them to provide such a […].
This article was published as a part of the Data Science Blogathon. Introduction More often than not, developers run into issues of an application running on one machine versus not running on another. Dockers help prevent this by ensuring the application runs on any machine if it works on yours. Simply put, if your job as […]. The post Building a simple Flask App using Docker vs Code appeared first on Analytics Vidhya.
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.
This article was published as a part of the Data Science Blogathon. Introduction Voting ensembles are the ensemble machine learning technique, one of the top-performing models among all machine learning algorithms. As voting ensembles are the most used ensemble techniques, there are lots of interview questions related to this topic that are asked in data […].
This article was published as a part of the Data Science Blogathon. Introduction Natural language processing (NLP) is the branch of computer science and, more specifically, the domain of artificial intelligence (AI) that focuses on providing computers the ability to understand written and spoken language in a way similar to that of humans. Combining computational linguistics […].
This article was published as a part of the Data Science Blogathon Introduction In this article, we will discuss DevOps, two phases of DevOps, its advantages, and why we need DevOps along with CI and CD Pipelines. Before DevOps, software development teams, quality assurance (QA) teams, security, and operations would test the code for several […].
This article was published as a part of the Data Science Blogathon. Introduction We, as data science and machine learning enthusiasts, have learned about various algorithms like Logistic Regression, Linear Regression, Decision Trees, Naive Bayes, etc. But at the same time, are we preparing for the interviews? As we know, the end goal is to […].
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?
This article was published as a part of the Data Science Blogathon. Introduction Requests in Python is a module that can be used to send all kinds of HTTP requests. It is straightforward to use and is a human-friendly HTTP Library. Using the requests library; we do not need to manually add the query string […]. The post Introduction to Requests Library in Python appeared first on Analytics Vidhya.
This article was published as a part of the Data Science Blogathon. Introduction Kats model-which is also developed by Facebook Research Team-supports the functionality of multi-variate time-series forecasting in addition to univariate time-series forecasting. Often we need to forecast a time series where we have input variables in addition to ‘time’; this is where the […].
This article was published as a part of the Data Science Blogathon. Introduction Any data science task starts with exploratory data analysis to learn more about the data, what is in the data and what is not. Having knowledge of different pandas functions certainly helps to complete the analysis in time. Therefore, I have listed […]. The post Pandas Functions You Should Know for Data Analysis appeared first on Analytics Vidhya.
This article was published as a part of the Data Science Blogathon. Introduction If you are a data scientist or a Python developer who sometimes wears the data scientist hat, you were likely required to work with some of these tools & technologies: Pandas, NumPy, PyArrow, and MongoDB. If you are new to these terms, […]. The post Using MongoDB with Pandas, NumPy, and PyArrow appeared first on Analytics Vidhya.
📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.
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