Unite.AI

SEPTEMBER 22, 2023

Jay Mishra is the Chief Operating Officer (COO) at Astera Software , a rapidly-growing provider of enterprise-ready data solutions. And then I found certain areas in computer science very attractive such as the way algorithms work, advanced algorithms. What initially attracted you to computer science?

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Large Language Models Automation Artificial Intelligence Artificial Intelligence 278

Pickl AI

DECEMBER 9, 2024

Summary: This article provides a comprehensive guide on Big Data interview questions, covering beginner to advanced topics. Introduction Big Data continues transforming industries, making it a vital asset in 2025. The global Big Data Analytics market, valued at $307.51 What is Big Data?

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Pickl AI

FEBRUARY 17, 2025

Introduction: The Reality of Machine Learning Consider a healthcare organisation that implemented a Machine Learning model to predict patient outcomes based on historical data. However, once deployed in a real-world setting, its performance plummeted due to data quality issues and unforeseen biases.

Machine Learning 52

Machine Learning Algorithm Explainability Data Quality 52

ODSC - Open Data Science

APRIL 28, 2023

But before AI/ML can contribute to enterprise-level transformation, organizations must first address the problems with the integrity of the data driving AI/ML outcomes. The truth is, companies need trusted data, not just big data. That’s why any discussion about AI/ML is also a discussion about data integrity.

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Pickl AI

JANUARY 12, 2025

A generative AI company exemplifies this by offering solutions that enable businesses to streamline operations, personalise customer experiences, and optimise workflows through advanced algorithms. Data forms the backbone of AI systems, feeding into the core input for machine learning algorithms to generate their predictions and insights.

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Pickl AI

OCTOBER 9, 2023

However, with the emergence of Machine Learning algorithms, the retail industry has seen a revolutionary shift in demand forecasting capabilities. This technology allows computers to learn from historical data, identify patterns, and make data-driven decisions without explicit programming.

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ODSC - Open Data Science

NOVEMBER 29, 2024

Artificial Intelligence (AI) stands at the forefront of transforming data governance strategies, offering innovative solutions that enhance data integrity and security. In this post, let’s understand the growing role of AI in data governance, making it more dynamic, efficient, and secure. You can connect with him on LinkedIn.

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IBM Journey to AI blog

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

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The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

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ODSC - Open Data Science

FEBRUARY 28, 2023

Going from Data to Insights LexisNexis At HPCC Systems® from LexisNexis® Risk Solutions you’ll find “a consistent data-centric programming language, two processing platforms, and a single, complete end-to-end architecture for efficient processing.” These tools are designed to help companies derive insights from big data.

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AWS Machine Learning Blog

JUNE 3, 2024

In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing. Custom Spark commands can also expand the over 300 built-in data transformations. Other analyses are also available to help you visualize and understand your data.

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Pickl AI

OCTOBER 10, 2024

Summary: Data transformation tools streamline data processing by automating the conversion of raw data into usable formats. These tools enhance efficiency, improve data quality, and support Advanced Analytics like Machine Learning. Why Are Data Transformation Tools Important?

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ETL Data Quality Machine Learning Business Intelligence 52

Pickl AI

JULY 29, 2024

It utilises the Hadoop Distributed File System (HDFS) and MapReduce for efficient data management, enabling organisations to perform big data analytics and gain valuable insights from their data. In a Hadoop cluster, data stored in the Hadoop Distributed File System (HDFS), which spreads the data across the nodes.

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Big Data Metadata Data Quality Machine Learning 52

Pragnakalp

APRIL 29, 2024

Step 3: Load and process the PDF data For this blog, we will use a PDF file to perform the QnA on it. We’ve selected a research paper titled “DEEP LEARNING APPLICATIONS AND CHALLENGES IN BIG DATA ANALYTICS,” which can be accessed at the following link: [link] Please download the PDF and place it in your working directory.

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Deep Learning Big Data Data Science LLM 59

Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms.

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Pickl AI

JUNE 4, 2024

Machine Learning This involves training algorithms on large datasets to learn from data without explicit programming. Big Data Analytics This involves analyzing massive datasets that are too large and complex for traditional data analysis methods.

Data Science 52

Data Science Data Scientist Big Data Machine Learning 52

Pickl AI

JUNE 24, 2024

Introduction In the age of big data, where information flows like a relentless river, the ability to extract meaningful insights is paramount. Association rule mining (ARM) emerges as a powerful tool in this data-driven landscape, uncovering hidden patterns and relationships between seemingly disparate pieces of information.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

It includes processes for monitoring model performance, managing risks, ensuring data quality, and maintaining transparency and accountability throughout the model’s lifecycle. After you have completed the data preparation step, it’s time to train the classification model.

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ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

Data Science 52

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Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Understanding Machine Learning algorithms and effective data handling are also critical for success in the field.

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Machine Learning Neural Network ML Engineer Algorithm 52

Pickl AI

DECEMBER 3, 2024

Summary: Data preprocessing in Python is essential for transforming raw data into a clean, structured format suitable for analysis. It involves steps like handling missing values, normalizing data, and managing categorical features, ultimately enhancing model performance and ensuring data quality.

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ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

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Data Science Big Data ETL Deep Learning 52

TransOrg Analytics

AUGUST 7, 2024

Challenges in Credit Risk Modeling Despite its importance, credit risk modelling faces several challenges: Data Quality and Availability: Accurate credit risk modelling relies on high-quality, comprehensive data. Only complete or updated data can lead to reliable predictions and informed decision-making.

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Neural Network Big Data Deep Learning Machine Learning 52

Pickl AI

DECEMBER 6, 2024

Issues such as data quality, resistance to change, and a lack of skilled personnel can hinder success. Key Takeaways Data quality is essential for effective Pricing Analytics implementation. Ensuring high-quality data collection processes is essential for reliable outcomes.

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Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently.

Data Science 52

Data Science Data Scientist ETL Machine Learning 52

Heartbeat

OCTOBER 25, 2023

Next-generation sequencing (NGS) platforms have dramatically increased the speed and reduced the cost of DNA sequencing, leading to the generation of vast amounts of genomic data. Integrating and analyzing data from multiple platforms and experiments pose challenges due to data formats, normalization techniques, and data quality differences.

Machine Learning 52

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Pickl AI

OCTOBER 15, 2024

Predictive Analytics Predictive analytics involves using statistical algorithms and Machine Learning techniques to forecast future events based on historical data. These technologies enable organisations to analyse vast amounts of data quickly and accurately.

Machine Learning 52

Machine Learning Big Data Artificial Intelligence Artificial Intelligence 52

Pickl AI

JANUARY 23, 2024

Machine Learning Explored and applied ML algorithms for intelligent solutions. Job options after MBA in Business Analytics Job role Description Average Annual Salary Data Analyst Analysing and interpreting complex data sets, Data Analysts are crucial in extracting meaningful insights that guide strategic decision-making.

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Data Scientist Machine Learning Business Intelligence Big Data 52

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. Machine Learning Algorithms : Uber uses Machine Learning to refine its algorithms continuously.

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Machine Learning Algorithm Natural Language Processing Data Analysis 52

Pickl AI

JULY 23, 2023

While unstructured data may seem chaotic, advancements in artificial intelligence and machine learning enable us to extract valuable insights from this data type. Big Data Big data refers to vast volumes of information that exceed the processing capabilities of traditional databases.

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Data Analysis Explainability Algorithm Machine Learning 52

Pickl AI

NOVEMBER 3, 2023

It is now the foundation for intelligent, data-driven decisions in present-day stock trading. Forecasts indicate that during the next five years, the global algorithmic trading market is expected to increase at a consistent rate of 8.53%. It went from simple rule-based systems to advanced data-driven algorithms.

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Artificial Intelligence Artificial Intelligence Algorithm AI 52

Pickl AI

JUNE 6, 2024

Data scrubbing is often used interchangeably but there’s a subtle difference. Cleaning is broader, improving data quality. This is a more intensive technique within data cleaning, focusing on identifying and correcting errors. Data scrubbing is a powerful tool within this cleaning service.

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ODSC - Open Data Science

JULY 13, 2023

For example, retailers could analyze and reveal trends much faster with a big data platform. It also can ensure they retain quality details since they don’t have to limit how much they collect. Quality Most retailers have dealt with irrelevant results even when using automatic processing systems like AI.

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Categorization Data Science Machine Learning Big Data 52

Pickl AI

OCTOBER 7, 2024

By leveraging Machine Learning algorithms, predictive analytics, and real-time data processing, AI can enhance decision-making processes and streamline operations. Quality Monitoring AI can enhance water quality monitoring by analysing data from various sources in real-time.

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AWS Machine Learning Blog

MAY 3, 2023

Feature engineering refers to the process where relevant variables are identified, selected, and manipulated to transform the raw data into more useful and usable forms for use with the ML algorithm used to train a model and perform inference against it. However, generalizing feature engineering is challenging.

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ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform. Check them out for free!

Data Science 52

Data Science NLP Machine Learning Data Analysis 52

Pickl AI

AUGUST 21, 2024

Advanced crawling algorithms allow them to adapt to new content and changes in website structures. Precision: Advanced algorithms ensure they accurately categorise and store data. This efficiency saves time and resources in data collection efforts. It is designed for scalability and can handle vast amounts of data.

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