AltexSoft

OCTOBER 18, 2022

Regardless of industry, data is considered a valuable resource that helps companies outperform their rivals, and healthcare is not an exception. In this post, we’ll briefly discuss challenges you face when working with medical data and make an overview of publucly available healthcare datasets, along with practical tasks they help solve.

Medical 52

Medical Datasets Machine Learning Hospitality 52

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.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

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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Data Science BI Business Intelligence Machine Learning 97

Knowledge Hut

APRIL 25, 2024

Big data vs machine learning is indispensable, and it is crucial to effectively discern their dissimilarities to harness their potential. Big Data vs Machine Learning Big data and machine learning serve distinct purposes in the realm of data analysis.

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

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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Project Healthcare Deep Learning Transportation 96

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.

Government 96

Government Education Unstructured Data Algorithm 96

AltexSoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. A powerful Big Data tool, Apache Hadoop alone is far from being almighty.

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Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

AUGUST 16, 2024

This will form a strong foundation for your Data Science career and help you gain the essential skills for processing and analyzing data, and make you capable of stepping into the Data Science industry. Let us look at some of the areas in Mathematics that are the prerequisites to becoming a Data Scientist.

Data Science 52

Data Science Hadoop Unstructured Data Programming Language 52

RandomTrees

NOVEMBER 25, 2024

Understanding Generative AI Generative AI describes an integrated group of algorithms that are capable of generating content such as: text, images or even programming code, by providing such orders directly. The considerable amount of unstructured data required Random Trees to create AI models that ensure privacy and data handling.

Telecommunication 52

Telecommunication IT Unstructured Data Data Mining 52

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.

Software Engineer 97

Software Engineer Software Engineering Data Science Engineering 97

Knowledge Hut

APRIL 23, 2024

View A broader view of data Narrower view of data Data Data is gleaned from diverse sources. Data is gleaned from structured and specific sources Volume Massive volumes of data Smaller volumes of data Analysis Entails techniques like data aggregation, fusion, etc.,

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

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.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

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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Deep Learning Machine Learning Unstructured Data Algorithm 52

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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Data Engineering Data Engineer Coding Project 98

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.

Unstructured Data 86

Unstructured Data Database Data Pipeline Architecture 86

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?

Deep Learning 40

Deep Learning Algorithm Machine Learning Datasets 40

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.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

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

Data Science MongoDB Programming Language Hadoop 52

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.

Machine Learning 52

Machine Learning Python Datasets Algorithm 52

Netflix Tech

APRIL 26, 2022

To achieve this, we rely on Machine Learning (ML) algorithms. ML algorithms can be only as good as the data that we provide to it. This post will focus on the large volume of high-quality data stored in Axion?—?our The Iceberg table created by Keystone contains large blobs of unstructured data.

Metadata 79

Metadata Datasets Machine Learning Designing 79

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?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

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.

Banking 52

Banking Deep Learning Machine Learning Finance 52

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!

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

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."

Data Science 52

Data Science Unstructured Data Medical Healthcare 52

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.

Hospitality 52

Hospitality Datasets Algorithm Machine Learning 52

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.),

Machine Learning 52

Machine Learning Engineering Algorithm Data Science 52

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.

Database-centric 52

Database-centric Data Science Machine Learning Algorithm 52

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.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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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Data Integration Architecture Amazon Web Services Machine Learning 69

ProjectPro

AUGUST 9, 2021

Top 20 Python Projects for Data Science Without much ado, it’s time for you to get your hands dirty with Python Projects for Data Science and explore various ways of approaching a business problem for data-driven insights. 1) Music Recommendation System on KKBox Dataset Music in today’s time is all around us.

Data Science 52

Data Science Python Project Datasets 52

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.

Machine Learning 52

Machine Learning Deep Learning Algorithm Data Mining 52

ProjectPro

MARCH 17, 2021

Machine learning makes use of a set of learning algorithms (supervised or unsupervised learning process) to analyze the data, interpret it, learn from it, and make the best possible business decisions based on the learnings. But how will the ML algorithm know which one is Apple and which one is Orange?

Deep Learning 52

Deep Learning Machine Learning Algorithm Data Science 52

Monte Carlo

JUNE 2, 2021

Data lakes almost always contain larger data sets, often with massive amounts of unstructured data. And while data engineers working in other tech stacks can leverage data testing tools like dbt and Great Expectations, scaling these solutions for the large datasets typical of data lakes can prove challenging.

Data Lake 52

Data Lake Machine Learning Unstructured Data Datasets 52

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.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

AltexSoft

OCTOBER 25, 2021

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. This allows machines to extract value even from unstructured data. Healthcare organizations generate a lot of text data. Source: Linguamatics.

Medical 52

Medical Healthcare Process Hospitality 52

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.

Scala 52

Scala Hospitality Healthcare Machine Learning 52

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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Data Cleanse Datasets Data Preparation Data Science 52