Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

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Knowledge Hut

JULY 28, 2023

Parameters Machine Learning (ML) Deep Learning (DL) Feature Engineering ML algorithms rely on explicit feature extraction and engineering, where human experts define relevant features for the model. DL models automatically learn features from raw data, eliminating the need for explicit feature engineering. What is Machine Learning?

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Rockset

APRIL 18, 2023

Organizations have continued to accumulate large quantities of unstructured data, ranging from text documents to multimedia content to machine and sensor data. Comprehending and understanding how to leverage unstructured data has remained challenging and costly, requiring technical depth and domain expertise.

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Unstructured Data Metadata Machine Learning SQL 105

Snowflake

APRIL 20, 2023

When asked what trends are driving data and AI , I explained two broad themes: The first is seeing more models and algorithms getting productionized and rolled out in interactive ways to the end user. Figure 1: Visual Question Answering Challenge data types and results.

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Knowledge Hut

MAY 23, 2024

Matlab: Matlab is a closed-source, high-performing, numerical, computational, simulation-making, multi-paradigm data science tool for processing mathematical and data-driven tasks. Through this tool, researchers and data scientists can perform matrix operations, analyze algorithmic performance, and render data statistical modeling.

Data Science 52

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ProjectPro

JULY 9, 2021

Suppose you’re among those fascinated by the endless possibilities of deep learning technology and curious about the popular deep learning algorithms behind the scenes of popular deep learning applications. Table of Contents Why Deep Learning Algorithms over Traditional Machine Learning Algorithms? What is Deep Learning?

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RandomTrees

JUNE 17, 2024

This article looks into AI’s different uses in financial fraud detection, with a focus on techniques involving anomaly detection, machine learning algorithms, and real-time data analysis that help safeguard the credibility of financial systems. It includes identifying unusual behaviors or patterns within datasets.

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Knowledge Hut

DECEMBER 22, 2023

A dataset is frequently represented as a matrix. Statistics Statistics are at the heart of complex machine learning algorithms in data science, identifying and converting data patterns into actionable evidence. Machine Learning Machine learning, a branch of data science, is used to model and derive conclusions from it.

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Knowledge Hut

MAY 31, 2023

AI Health Engine Language: Python Data set: CSV file Source code: Patient-Selection-for-Diabetes-Drug-Testing Artificial intelligence (AI) in healthcare is called the "AI Health Engine." The privacy and security of patient data and ensuring that AI algorithms are accurate, dependable, and impartial must be overcome.

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Knowledge Hut

DECEMBER 26, 2023

These skills are essential to collect, clean, analyze, process and manage large amounts of data to find trends and patterns in the dataset. The dataset can be either structured or unstructured or both. In this article, we will look at some of the top Data Science job roles that are in demand in 2024.

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AltexSoft

MAY 27, 2022

A large hospital group partnered with Intel, the world’s leading chipmaker, and Cloudera, a Big Data platform built on Apache Hadoop , to create AI mechanisms predicting a discharge date at the time of admission. The built-in algorithm learns from every case, enhancing its results over time. Inpatient data anonymization.

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Cloudera

DECEMBER 19, 2023

Improve dataset quality. Ensure you can trust your data by using only diverse, high-quality training data that represents different demographics and viewpoints. Make sure to audit data regularly. Have plans to address issues like harmful content generation, data abuse, and algorithmic bias.

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Knowledge Hut

DECEMBER 26, 2023

What i s Data Science and Why is it Important? Data Science is the study of extracting insights from massive amounts of data using various scientific approaches, processes and algorithms. The development of big data, data analysis, and quantitative statistics has given rise to the term "data science."

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Edureka

JANUARY 18, 2024

For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? Data science is the study of data to extract knowledge and insights from structured and unstructured data using scientific methods, processes, and algorithms.

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Knowledge Hut

JANUARY 24, 2024

This blog offers an exclusive glimpse into the daily rituals, challenges, and moments of triumph that punctuate the professional journey of a data scientist. The primary objective of a data scientist is to analyze complex datasets to uncover patterns, trends, and valuable information that can aid in informed decision-making.

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AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

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AltexSoft

FEBRUARY 21, 2023

This blog post will delve into the challenges, approaches, and algorithms involved in hotel price prediction. Hotel price prediction is the process of using machine learning algorithms to forecast the rates of hotel rooms based on various factors such as date, location, room type, demand, and historical prices. Data relevance.

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Monte Carlo

NOVEMBER 9, 2023

We *know* what we’re putting in (raw, often unstructured data) and we *know* what we’re getting out, but we don’t know how it got there. Fine tuning is the process of training an existing LLM on a smaller, task-specific and labeled dataset, adjusting model parameters and embeddings based on this new data.

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ProjectPro

JANUARY 28, 2022

In data science, algorithms are usually designed to detect and follow trends found in the given data. The modeling follows from the data distribution learned by the statistical or neural model. In real life, the features of data points in any given domain occur within some limits.

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AltexSoft

MAY 12, 2022

Aiming at understanding sound data, it applies a range of technologies, including state-of-the-art deep learning algorithms. Another application of musical audio analysis is genre classification: Say, Spotify runs its proprietary algorithm to group tracks into categories (their database holds more than 5,000 genres ).

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Knowledge Hut

JANUARY 18, 2024

This field uses several scientific procedures to understand structured, semi-structured, and unstructured data. It entails using various technologies, including data mining, data transformation, and data cleansing, to examine and analyze that data.

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Knowledge Hut

MAY 2, 2024

It achieves this using abstraction layer called RDD (Resilient Distributed Datasets) in combination with DAG, which is built to handle failures of tasks or even node failures. Streaming Data: Streaming is basically unstructured data produced by different types of data sources.

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Knowledge Hut

APRIL 26, 2024

Let's take a look at all the fuss about data science , its courses, and the path to the future. What is Data Science? In order to discover insights and then analyze multiple structured and unstructured data, Data Science requires the use of different instruments, algorithms and principles.

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Knowledge Hut

JANUARY 19, 2024

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. That's the promise of a career in data science.

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Knowledge Hut

APRIL 23, 2024

Whether you know it or not, this article will help you understand how companies ride the big data wave without merely getting stuck by the massive volume. Go for the best Big Data courses and work on ral-life projects with actual datasets.

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U-Next

SEPTEMBER 9, 2022

The platform distributes Hadoop large data and analytics operations among computer cluster nodes, breaking them down into smaller workloads that may be handled in parallel. Hadoop can scale up from a single server to thousands of servers and analyze organized and unstructured data. . What is Hadoop in Big Data? .

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Knowledge Hut

JANUARY 25, 2024

What is Data Cleaning? Data cleaning, also known as data cleansing, is the essential process of identifying and rectifying errors, inaccuracies, inconsistencies, and imperfections in a dataset. It involves removing or correcting incorrect, corrupted, improperly formatted, duplicate, or incomplete data.

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Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

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U-Next

AUGUST 8, 2022

In contrast, information mining is the practice of trying to remove information or intriguing patterns from unstructured data. Learning algorithms are applied in this processing system. The supervised learning is then given a fresh dataset, allowing the algorithm to analyse the labelled data and provide a successful result.

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ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. Datasets like Google Local, Amazon product reviews, MovieLens, Goodreads, NES, Librarything are preferable for creating recommendation engines using machine learning models. Let the FOMO kick in!

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Knowledge Hut

JUNE 26, 2023

Since there are numerous ways to approach this task, it encourages originality in one's approach to data analysis. Moreover, this project concept should highlight the fact that there are many interesting datasets already available on services like GCP and AWS. Source: Use Stack Overflow Data for Analytic Purposes 4.

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Striim

SEPTEMBER 11, 2024

A well-designed data pipeline ensures that data is not only transferred from source to destination but also properly cleaned, enriched, and transformed to meet the specific needs of AI algorithms. Why are data pipelines important? Where does Striim Come into Play When Building Data Pipelines?

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ProjectPro

DECEMBER 21, 2021

The machine learning career path is perfect for you if you are curious about data, automation, and algorithms, as your days will be crammed with analyzing, implementing, and automating large amounts of knowledge. This includes knowledge of data structures (such as stack, queue, tree, etc.),

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Knowledge Hut

JANUARY 22, 2024

Data science is a field of study that combines industry expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data scientists apply machine learning algorithms to numbers, text, images, video, audio, and more to create artificial intelligence (AI) systems.

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Striim

AUGUST 31, 2023

The goal of kappa architecture is to reduce the cost of data integration by providing an efficient and real-time way of managing large datasets. Additionally, it allows for efficient processing of both real-time and historical data which eliminates the need for multiple versions of the same dataset or manually managed systems.

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Knowledge Hut

MAY 9, 2024

In this blog post, we will look at some of the world's highest paying data science jobs, what they entail, and what skills and experience you need to land them. What is Data Science? Data science also blends expertise from various application domains, such as natural sciences, information technology, and medicine.

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Knowledge Hut

OCTOBER 26, 2023

It comes with in-built ML algorithms that do not require label data and leverages semantic search to simplify tasks. When AWS is used along with nearest-neighbor algorithms, you can get relevant recommendations and accurate results. This dataset can be downloaded in two formats: Parquet and TAV. Source code: GitHub 5.

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