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

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.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

AltexSoft

MAY 12, 2022

Particularly, we’ll explain how to obtain audio data, prepare it for analysis, and choose the right ML model to achieve the highest prediction accuracy. But first, let’s go over the basics: What is the audio analysis, and what makes audio data so challenging to deal with. Labeling of audio data in Audacity.

Machine Learning 122

Machine Learning Building Deep Learning Datasets 122

ProjectPro

JANUARY 24, 2023

They were able to use SageMaker's pre-built algorithms and libraries to quickly and easily train their ML models and then deploy them to the edge (i.e., SageMaker also supports building customized algorithms and frameworks and allows for flexible distributed training options.

Building 52

Building Algorithm Machine Learning AWS 52

Precisely

SEPTEMBER 26, 2024

However, achieving success in AI projects isn’t just about deploying advanced algorithms or machine learning models. The real challenge lies in ensuring that the data powering your projects is AI-ready. Above all, you must remember that trusted AI starts with trusted data. The impact?

Project 75

Project Government Data Governance Data Integration 75

Knowledge Hut

NOVEMBER 27, 2023

Additionally, proficiency in probability, statistics, programming languages such as Python and SQL, and machine learning algorithms are crucial for data science success. Through the article, we will learn what data scientists do, and how to transits to a data science career path. What Do Data Scientists Do?

Data Science 52

Data Science Datasets Machine Learning Portfolio 52

AltexSoft

OCTOBER 30, 2021

Data engineers are programmers that create software solutions with big data. They’re integral specialists in data science projects and cooperate with data scientists by backing up their algorithms with solid data pipelines. Juxtaposing data scientist vs engineer tasks. Data preparation and cleaning.

Data Engineer 98

Data Engineer Data Engineering Engineering Machine Learning 98

AltexSoft

AUGUST 25, 2021

But today’s programs, armed with machine learning and deep learning algorithms, go beyond picking the right line in reply, and help with many text and speech processing problems. For example, tokenization (splitting text data into words) and part-of-speech tagging (labeling nouns, verbs, etc.) Preparing an NLP dataset.

Process 139

Process Deep Learning Datasets Machine Learning 139

ProjectPro

AUGUST 30, 2022

Top 5 Loan Prediction Datasets to Practice Loan Prediction Projects Univ.AI Top 5 Loan Prediction Datasets to Practice Loan Prediction Projects Univ.AI Top 5 Loan Prediction Datasets to Practice Loan Prediction Projects Univ.AI Which algorithm is best for Loan Prediction using Machine Learning?

Machine Learning 52

Machine Learning Coding Project Datasets 52

AltexSoft

JUNE 21, 2023

Machine learning employs sophisticated algorithms to anticipate future trends and accurately predict ADRs for hotels and vacation rentals. For example, at AltexSoft, our team developed two algorithms to support Rakuten Travel , Japan’s leading online booking platform that owns several hotels. Data shortage and poor quality.

Hospitality 52

Hospitality Management Machine Learning Datasets 52

Knowledge Hut

JANUARY 29, 2024

On the other hand, data science is a technique that collects data from various resources for data preparation and modeling for extensive analysis. Cloud Computing provides storage, scalable compute, and network bandwidth to handle substantial data applications.

Cloud Computing 98

Cloud Computing Data Science Cloud Amazon Web Services 98

AltexSoft

MAY 12, 2021

Particularly, we’ll present our findings on what it takes to prepare a medical image dataset, which models show best results in medical image recognition , and how to enhance the accuracy of predictions. The most advanced AI algorithms achieved the accuracy of almost 97 percent. Spoiler: we finally opted for public datasets.

Medical 72

Medical Healthcare Datasets Machine Learning 72

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

Knowledge Hut

OCTOBER 27, 2023

Microsoft created Power BI, a business analytics tool that enables users to visualize and analyze data from various sources quickly and interactively. It provides a wide range of features and functionalities, including data preparation, data modeling, data visualization, and collaboration tools.

BI 52

BI Project Datasets Healthcare 52

Edureka

JUNE 12, 2024

It supports various algorithms, such as supervised, unsupervised, and reinforcement learning, allowing users to create predictive models for tasks such as classification, regression, and clustering. Now, let’s walk through a typical workflow: You start by collecting data from various sources and storing it in Azure.

Machine Learning 52

Machine Learning Deep Learning Healthcare Finance 52

AltexSoft

NOVEMBER 15, 2022

Dataset preparation and construction. The starting point of any machine learning task is data. A lot of data, to be exact. A lot of quality data, to be even more exact. To learn the basics, you can read our dedicated article on how data is prepared for machine learning or watch a short video.

Hospitality 52

Hospitality Building Datasets Machine Learning 52

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.

Data Science 52

Data Science Data Architect Data Mining Programming Language 52

ProjectPro

JANUARY 31, 2023

Overfitting occurs when an ML model yields accurate results for training examples but not for unseen data. It can be prevented in many ways, for instance, by choosing another algorithm, optimizing the hyperparameters, and changing the model architecture. Table of Contents What is Data Augmentation in Deep Learning?

Deep Learning 52

Deep Learning Datasets Machine Learning Data 52

Knowledge Hut

FEBRUARY 1, 2024

You cannot expect your analysis to be accurate unless you are sure that the data on which you have performed the analysis is free from any kind of incorrectness. Data cleaning in data science plays a pivotal role in your analysis. It’s a fundamental aspect of the data preparation stages of a machine learning cycle.

Data Science 52

Data Science Process Data Cleanse Datasets 52

AltexSoft

NOVEMBER 17, 2021

Training neural networks and implementing them into your classifier can be a cumbersome task since they require knowledge of deep learning and quite large datasets. Stating categories and collecting training dataset. Before a model can classify any documents, it has to be trained on historical data tagged with category labels.

Machine Learning 75

Machine Learning Insurance Medical Healthcare 75

Edureka

JANUARY 23, 2023

Data mining is analysing large volumes of data available in the company’s storage systems or outside to find patterns to help them improve their business. The process uses powerful computers and algorithms to execute statistical analysis of data. They fine-tune the algorithm at this stage to get the best results.

Data Mining 52

Data Mining Banking Retail Medical 52

Knowledge Hut

DECEMBER 7, 2023

Data Preprocessing: Prepare and clean the data. This may include handling missing values, outliers, and transforming the data into a format suitable for AI algorithms. Model Selection: Choose the appropriate AI algorithm or framework that aligns with the project's objectives.

Machine Learning 52

Machine Learning Algorithm Medical Government 52

AltexSoft

DECEMBER 21, 2021

A label or a tag is a descriptive element that tells a model what an individual data piece is so it can learn by example. In this case, the training dataset will consist of multiple songs with labels showing genres like pop, jazz, rock, etc. So, what challenges does data labeling involve? Data labeling challenges.

Machine Learning 52

Machine Learning Process Raw Data Datasets 52

Knowledge Hut

JUNE 28, 2023

By examining these factors, organizations can make informed decisions on which approach best suits their data analysis and decision-making needs. Parameter Data Mining Business Intelligence (BI) Definition The process of uncovering patterns, relationships, and insights from extensive datasets.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

AltexSoft

MARCH 18, 2022

Supervised learning is training a machine learning model using the labeled dataset. Organic labels are often available in data, but a process may involve a human expert that adds tags to raw data to show a model the target attributes (answers). Supervised vs unsupervised vs semi-supervised machine learning in a nutshell.

Datasets 52

Datasets Machine Learning Algorithm Raw Data 52

AltexSoft

MAY 5, 2023

AI in a nutshell Artificial Intelligence (AI) , at its core, is a branch of computer science that focuses on developing algorithms and computer systems capable of performing tasks that typically require human intelligence. Deep Learning is a subset of machine learning that focuses on building complex algorithms named deep neural networks.

Machine Learning 59

Machine Learning Hospitality Algorithm Deep Learning 59

Cloudera

DECEMBER 17, 2020

When many businesses start their journey into ML and AI, it’s common to place a lot of energy and focus on the coding and data science algorithms themselves. In August 2020 we released CDP Data Engineering (DE) — our answer to enabling fast, optimized, and automated data engineering for analytic workloads.

Machine Learning 82

Machine Learning Data Science Data Pipeline Raw Data 82

ProjectPro

JANUARY 31, 2023

MapReduce is a Hadoop framework used for processing large datasets. Another name for it is a programming model that enables us to process big datasets across computer clusters. This program allows for distributed data storage, simplifying complex processing and vast amounts of data. Explain the data preparation process.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Rockset

JUNE 17, 2021

Netflix has built content recommendation algorithms that are responsible for 80% of the content streamed on their platform, saving the company $1B annually ( Dataconomy ). As operational databases were not designed for analytics, data is replicated to Rockset and automatically indexed for fast search, aggregations and joins.

Data Lake 40

Data Lake Architecture Data Preparation Database 40

Picnic Engineering

MAY 23, 2023

In this article, we’ll share insights from the Advanced Analytics and Algorithms (AAA) team’s two-day hackathon, where one of the hackathon teams explored and benchmarked three different types of models for large-scale routing of customer feedback with text classification.

Machine Learning 72

Machine Learning Algorithm Deep Learning Architecture 72

U-Next

AUGUST 11, 2022

It’s a study of Computer Algorithms, which helps self-improvement through experiences. It builds a model based on Sample data and is designed to make predictions and decisions without being programmed for it. Artificial Intelligence is achieved through the techniques of Machine Learning and Deep Learning.

Medical 52

Medical Computer Science Scala Machine Learning 52

ProjectPro

AUGUST 24, 2021

And if you are aspiring to become a data engineer, you must focus on these skills and practice at least one project around each of them to stand out from other candidates. Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

Knowledge Hut

JUNE 20, 2023

Analyze trends and patterns Conduct in-depth data analysis, then present the findings. Assemble data for predictive and prescriptive modeling. Construct prototypes and algorithms Combine raw data from many sources. Investigate methods to improve data quality and reliability.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

ProjectPro

NOVEMBER 15, 2021

In addition to analytics and data science, RAPIDS focuses on everyday data preparation tasks. This features a familiar DataFrame API that connects with various machine learning algorithms to accelerate end-to-end pipelines without incurring the usual serialization overhead. Trino Source: trino.io

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

SEPTEMBER 13, 2023

In the world of machine learning , there’s a well-known saying, “An ML model is only as good as the training data you feed it with.” It points out the critical role that data quality plays in the outcomes you get from these algorithms. Watch our video about data preparation for ML tasks to learn more about this.

Engineering 59

Engineering Hospitality Transportation Algorithm 59

Netflix Tech

OCTOBER 18, 2019

As with other traditional machine learning and deep learning paths, a lot of what the core algorithms can do depends upon the support they get from the surrounding infrastructure and the tooling that the ML platform provides. they were able to reframe the problem as a straight-forward black-box optimization problem.

Algorithm 51

Algorithm Architecture Machine Learning Deep Learning 51

ProjectPro

DECEMBER 22, 2016

Data analysis involves data cleaning. Results of data mining are not always easy to interpret. Data analysts interpret the results and convey the to the stakeholders. Data mining algorithms automatically develop equations. Data analysts have to develop their own equations based on the hypothesis.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52