Smart Data Collective

JULY 19, 2019

While conversations with chatbots once felt frustrating, repetitive, and a little too robotic, more sophisticated AI-powered chatbots use natural language processing (NLP) to have more natural, authentic conversations and to genuinely “understand” their customers’ needs.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

He has extensive experience developing enterprise-scale data architectures and governance strategies using both proprietary and native AWS platforms, as well as third-party tools. Previously, Karam developed big-data analytics applications and SOX compliance solutions for Amazons Fintech and Merchant Technologies divisions.

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AWS Machine Learning Blog

JANUARY 30, 2025

The team developed an innovative solution to streamline grant proposal review and evaluation by using the natural language processing (NLP) capabilities of Amazon Bedrock. Ben West is a hands-on builder with experience in machine learning, big data analytics, and full-stack software development.

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Data Science Connect

JULY 25, 2023

Continuous monitoring allows businesses to adapt quickly to changing risk landscapes and make data-driven adjustments to their risk management approach. These technologies enable real-time risk monitoring, early warning systems, and predictive modeling, empowering organizations to stay ahead of potential threats.

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AWS Machine Learning Blog

OCTOBER 5, 2023

His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering. His research interest is in systems, high-performance computing, and big data analytics.

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Smart Data Collective

SEPTEMBER 8, 2020

Big data analytics tools will help you see how well they work. Think of a specific theme, like natural wellness, adaptogenic plants, or an in-depth look into changing cultural perspectives on hemp—add some personality and voilà ! . #3 Create Your Own Podcast. No great writers on your team? 5 Partner with Local Businesses.

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Data Science Dojo

JULY 3, 2024

Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing. Artificial Intelligence : Concepts of AI include neural networks, natural language processing (NLP), and reinforcement learning.

Data Science 150

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Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

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Flipboard

OCTOBER 25, 2023

AWS AI services are designed to extract metadata from different types of unstructured data. The following are the most commonly used services for unstructured data processing: Amazon Comprehend – This natural language processing (NLP) service uses ML to extract metadata from text data.

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Pickl AI

OCTOBER 25, 2023

Machine Learning algorithms enable systems to learn and improve from data without being explicitly programmed. Natural Language Processing AI technologies, like Natural Language Processing (NLP), enable computers to understand, interpret, and generate human language.

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Pickl AI

JULY 20, 2023

Prescriptive Analytics Projects: Prescriptive analytics takes predictive analysis a step further by recommending actions to optimize future outcomes. NLP techniques help extract insights, sentiment analysis, and topic modeling from text data. Create machine learning models to quickly identify and stop fraudulent transactions.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

As AI adoption continues to accelerate, developing efficient mechanisms for digesting and learning from unstructured data becomes even more critical in the future. This could involve better preprocessing tools, semi-supervised learning techniques, and advances in natural language processing.

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ODSC - Open Data Science

SEPTEMBER 19, 2024

Streamlining Government Regulatory Responses with Natural Language Processing, GenAI, and Text Analytics Through text analytics, linguistic rules are used to identify and refine how each unique statement aligns with a different aspect of the regulation. How can big data analytics help?

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Pickl AI

DECEMBER 2, 2024

Machine Learning Algorithms: These algorithms can identify patterns in data and make predictions based on historical trends. Natural Language Processing (NLP): NLP techniques analyse textual data from sources like customer reviews or social media posts to derive sentiment analysis or topic modelling.

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Pickl AI

NOVEMBER 25, 2024

Machine Learning Algorithms: These algorithms can identify patterns in data and make predictions based on historical trends. Natural Language Processing (NLP): NLP techniques analyse textual data from sources like customer reviews or social media posts to derive sentiment analysis or topic modelling.

Big Data 52

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Pickl AI

SEPTEMBER 11, 2024

Specialised Knowledge One key advantage of pursuing a master’s degree in Data Science is the ability to acquire specialised knowledge. Unlike a bachelor’s program, which provides a broad overview, a master’s program delves deep into specific areas such as predictive analytics, natural language processing, or Artificial Intelligence.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

Raj provided technical expertise and leadership in building data engineering, big data analytics, business intelligence, and data science solutions for over 18 years prior to joining AWS. He helps customers architect and build highly scalable, performant, and secure cloud-based solutions on AWS.

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How to Learn Machine Learning

APRIL 15, 2023

These computer programs use natural language processing to understand and respond to customer inquiries. In this article, we will explore the ways in which AI is being used in the tourism industry and how it is changing the way we travel. How AI is Used in the Tourism Industry 1.

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Pickl AI

SEPTEMBER 24, 2024

This blog delves into how Uber utilises Data Analytics to enhance supply efficiency and service quality, exploring various aspects of its approach, technologies employed, case studies, challenges faced, and future directions. Customer Feedback Analysis Uber actively collects feedback from riders after each trip through its app.

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How to Learn Machine Learning

JUNE 21, 2024

It uses natural language processing (NLP) and AI systems to parse and interpret complex software documentation and user stories, converting them into executable test cases. Integration with emerging technologies Seamless combination of AI with IoT, big data analytics, and cloud computing.

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IBM Journey to AI blog

JULY 6, 2023

Healthcare companies are using data science for breast cancer prediction and other uses. One ride-hailing transportation company uses big data analytics to predict supply and demand, so they can have drivers at the most popular locations in real time.

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IBM Journey to AI blog

MAY 17, 2024

A full one-third of consumers found their early customer support and chatbot experiences that use natural language processing (NLP) so disappointing that they didn’t want to engage with the technology again. And  And the centrality of these experiences isn’t limited to B2C vendors.

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AWS Machine Learning Blog

MAY 3, 2023

He has extensive experience in Big Data Analytics, Distributed Computing, and Natural Language Processing. Sharmo Sarkar is a Senior Manager at Vericast. He leads the Cloud Machine Learning Platform and the Marketing Platform ML R&D Teams at Vericast.

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Pickl AI

SEPTEMBER 18, 2024

AI technologies, such as Machine Learning (ML) and natural language processing (NLP), have gained traction to protect, detect and respond to threats. While quantum computers could potentially break existing encryption methods, AI may assist in developing quantum-resistant encryption techniques that safeguard sensitive data.

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Pickl AI

JULY 18, 2023

Its simplicity, versatility, and extensive range of libraries make it a favorite choice among Data Scientists. However, with libraries like NumPy, Pandas, and Matplotlib, Python offers robust tools for data manipulation, analysis, and visualization. Q: What are the advantages of using Julia in Data Science?

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Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

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DagsHub

NOVEMBER 11, 2024

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. Tools like Unstructured.io

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Pickl AI

JANUARY 16, 2024

Trends in Data Analytics career path Trends Key Information Market Size and Growth CAGR Big Data Analytics Dealing with vast datasets efficiently. Cloud-based Data Analytics Utilising cloud platforms for scalable analysis. Value in 2022 – $271.83 billion In 2023 – $307.52 billion 26.4%

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Pickl AI

JULY 10, 2023

R’s machine learning capabilities allow for model training, evaluation, and deployment. · Text Mining and Natural Language Processing (NLP): R offers packages such as tm, quanteda, and text2vec that facilitate text mining and NLP tasks.

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Dataversity

FEBRUARY 16, 2022

Next in our blog series exploring interesting analytics use cases, we examine how machine learning algorithms dictate the music we listen to every day. In 2019, the music streaming market was valued at $12,831.2 million – a figure that’s expected to nearly double by 2027.

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ODSC - Open Data Science

FEBRUARY 15, 2024

Large language models have taken the world by storm, offering impressive capabilities in natural language processing. However, while these models are powerful, they can often benefit from fine-tuning or additional training to optimize performance for specific tasks or domains.

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Pickl AI

DECEMBER 4, 2024

This explosive growth is driven by the increasing volume of data generated daily, with estimates suggesting that by 2025, there will be around 181 zettabytes of data created globally.

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Pickl AI

SEPTEMBER 5, 2024

Data Scientists can use Azure Data Factory to prepare data for analysis by creating data pipelines that ingest data from multiple sources, clean and transform it, and load it into Azure data stores. Azure Cognitive Services offers ready-to-use models that seamlessly integrate into existing data workflows.

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The MLOps Blog

AUGUST 11, 2023

Standard ML pipeline | Source: Author Advantages and disadvantages of directed acyclic graphs architecture Using DAGs provides an efficient way to execute processes and tasks in various applications, including big data analytics, machine learning, and artificial intelligence, where task dependencies and the order of execution are crucial.

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Mlearning.ai

AUGUST 18, 2023

Data science in healthcare allows physicians to access patients’ health data, see the change over time, and tweak the treatment plan if something goes wrong. Utilizing big data analytics allows medical professionals to take advantage of historical information and get valuable insights.

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Dataconomy

FEBRUARY 11, 2025

AI summers, such as those driven by advancements in deep learning, increased computational power, and big data analytics, have repeatedly revived interest and funding. Recent AI summers have been fueled by key innovations, including deep learning, increased computational power, and advancements in big data analytics.

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Dataconomy

APRIL 13, 2025

Vector databases are specialized systems designed to effectively store, search, and manage high-dimensional vector data crucial for big data solutions and machine learning applications. Semantic search Semantic search leverages natural language processing (NLP) to enhance search capabilities beyond mere keyword matching.

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