Knowledge Hut

MAY 31, 2023

Artificial intelligence (AI) projects are software-based initiatives that utilize machine learning, deep learning, natural language processing, computer vision, and other AI technologies to develop intelligent programs capable of performing various tasks with minimal human intervention. Let us get started!

Project 96

Project Healthcare Deep Learning Transportation 96

Knowledge Hut

MAY 2, 2024

It means computers learn and there are many concepts, methods, algorithms and processes involved in making this happen. Let us try to understand some of the more important machine learning terms. Three concepts – artificial intelligence, machine learning and deep learning – are often thought to be synonymous.

Machine Learning 98

Machine Learning IT Deep Learning Algorithm 98

Confluent

FEBRUARY 6, 2019

Uber expanded Michelangelo “to serve any kind of Python model from any source to support other Machine Learning and Deep Learning frameworks like PyTorch and TensorFlow [instead of just using Spark for everything].”. Data scientists love Python, period. These standards have pros and cons.

Machine Learning 107

Machine Learning Python Kafka Java 107

Cloudera

NOVEMBER 19, 2020

Analyzing historical data is an important strategy for anomaly detection. The modeling process begins with data collection. Here, Cloudera Data Flow is leveraged to build a streaming pipeline which enables the collection, movement, curation, and augmentation of raw data feeds.

Government 119

Government Machine Learning Algorithm Raw Data 119

Knowledge Hut

JULY 4, 2023

It involves extracting meaningful features from the data and using them to make informed decisions or predictions. Data Collection and Pre-processing The first step is to collect the relevant data that contains the patterns of interest. The steps involved in it can be summarized as follows: 1.

Machine Learning 98

Machine Learning Medical Algorithm Deep Learning 98

Knowledge Hut

MAY 2, 2024

Analysis of data includes Condensation, Summarization, Conclusion etc., The Interpretation step includes drawing conclusions from the data collected as the figures don’t speak for themselves. Statistics used in Machine Learning is broadly divided into two categories, based on the type of analyses they perform on the data.

Machine Learning 98

Machine Learning Algorithm Datasets Python 98

AltexSoft

MAY 27, 2022

MIMIC standing for Medical Information Mart for Intensive Care is a freely available database of medical data collected from patients in intensive care units (ICU). There are numerous studies describing experiments with deep learning models trained to predict LOS. MIMIC database. several others.

Hospitality 98

Hospitality Medical Healthcare Algorithm 98

Knowledge Hut

JUNE 3, 2024

So, with the advent of the internet, this analysis is becoming increasingly sophisticated with the use of artificial intelligence , or AI and machine learning. Moreover, as the economy evolves, learning consumer behavior will be the chief tool for marketing. We are at the very cusp of the data collection explosion in such a case.

Programming Language 96

Programming Language Data Science Entertainment Banking 96

Knowledge Hut

DECEMBER 26, 2023

They collect and extract data from warehouses using querying techniques, analyze this data and create summary reports of the company's current standings. They suggest recommendations to management to increase the efficiency of the business and develop new analytical models to standardize data collection.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Knowledge Hut

MAY 1, 2024

If the general idea of stand-up meetings and sprint meetings is not taken into consideration, a day in the life of a data scientist would revolve around gathering data, understanding it, talking to relevant people about the data, asking questions about it, reiterating the requirement and the end product, and working on how it can be achieved.

Algorithm 98

Algorithm Data Science Raw Data Computer Science 98

Cloudera

FEBRUARY 4, 2019

With the rise of streaming architectures and digital transformation initiatives everywhere, enterprises are struggling to find comprehensive tools for data management to handle high volumes of high-velocity streaming data. He currently works at Cloudera, managing their Data-in-Motion product line.

Data Ingestion 73

Data Ingestion Retail Kafka Data Lake 73

Knowledge Hut

JANUARY 18, 2024

These professionals are capable of handling feature engineering, getting the data, and model building. They also ensure the efficient application of the model for making relevant predictions using the data collected through various methods.

Data Science 96

Data Science Computer Science Programming Language Machine Learning 96

Knowledge Hut

FEBRUARY 29, 2024

Learning inferential statistics website: wallstreetmojo.com, kdnuggets.com Learning Hypothesis testing website: stattrek.com Start learning database design and SQL. A database is a structured data collection that is stored and accessed electronically.

Data Science 98

Data Science Datasets Machine Learning Database Design 98

ProjectPro

JANUARY 31, 2023

Data scientists and machine learning engineers often come across this scenario where the data for their project is not sufficient for training a machine learning model, often resulting in poor performance. Table of Contents What is Data Augmentation in Deep Learning?

Deep Learning 52

Deep Learning Datasets Machine Learning Data 52

ProjectPro

APRIL 17, 2015

Last year when Twitter and IBM announced their partnership it seemed an unlikely pairing, but the recent big data news on New York Times about this partnership took a leap forward with IBM’s Watson all set to mine Tweets for sentiments. Deep learning involves ingesting big data to neural networks to receive predictions in response.

Big Data 52

Big Data Data Analysis NoSQL Deep Learning 52

Edureka

MARCH 26, 2025

Non-linear Transformation: By utilizing activation functions such as ReLU, sigmoid, or tanh, hidden layers augment the network’s ability to learn from data that isn’t limited to linearly separable information. Data Preprocessing: Tools for cleaning, normalizing, and augmenting data to ensure accuracy and relevance.

Raw Data 40

Raw Data Architecture Deep Learning Finance 40

RandomTrees

DECEMBER 12, 2023

It is necessary to tailor sensitive or regulated data to specific conditions to achieve the results that authentic data cannot deliver. Computer vision can generate synthetic data in two ways. A 3D renderer will automatically annotate synthetic data after getting rendered in 3D.

Deep Learning 52

Deep Learning Datasets Healthcare Algorithm 52

U-Next

AUGUST 11, 2022

Artificial Intelligence is achieved through the techniques of Machine Learning and Deep Learning. Machine Learning (ML) is a part of Artificial Intelligence. It builds a model based on Sample data and is designed to make predictions and decisions without being programmed for it. is highly beneficial.

Medical 52

Medical Computer Science Machine Learning Scala 52

WeCloudData

OCTOBER 19, 2021

With these data tools in place, the WeCloudData team was able to: Process the raw user clickstream data with Python & Spark to develop an array of recommender models. These models utilized traditional methods like content-based filtering and collaborative filtering, as well as more advanced deep learning techniques with BERT.

Consulting 52

Consulting Systems NoSQL Raw Data 52

WeCloudData

OCTOBER 19, 2021

With these data tools in place, the WeCloudData team was able to: Process the raw user clickstream data with Python & Spark to develop an array of recommender models. These models utilized traditional methods like content-based filtering and collaborative filtering, as well as more advanced deep learning techniques with BERT.

Consulting 52

Consulting Systems NoSQL Raw Data 52

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use.

Data Governance 75

Data Governance Government Machine Learning Data Science 75

Cloudera

FEBRUARY 16, 2022

We can think of model lineage as the specific combination of data and transformations on that data that create a model. This maps to the data collection, data engineering, model tuning and model training stages of the data science lifecycle. So, we have workspaces, projects and sessions in that order.

Machine Learning 85

Machine Learning Algorithm Government Metadata 85

AltexSoft

OCTOBER 18, 2022

No wonder publicly available health datasets are relatively rare and attract much attention from researchers, data scientists, and companies working on medical AI solutions. Below, we’ll explore data collections the Internet has to offer and the practical tasks they help solve. Older Adults Health Data Collection.

Medical 52

Medical Datasets Machine Learning Hospitality 52

Knowledge Hut

JUNE 26, 2023

Use Stack Overflow Data for Analytic Purposes Project Overview: What if you had access to all or most of the public repos on GitHub? As part of similar research, Felipe Hoffa analysed gigabytes of data spread over many publications from Google's BigQuery data collection. Python source code for Big Data can be written.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

AltexSoft

JULY 27, 2021

Google singles out four key phases through which a recommender system processes data. They are information collection, storing, analysis, and filtering. Data collection. The initial phase involves gathering relevant data to create a user profile or model for prediction tasks. Let’s have a closer look at each phase.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

U-Next

SEPTEMBER 13, 2022

A multidisciplinary field called Data Science involves unprocessed data mining, its analysis, and discovering patterns utilized to extract meaningful information. The fundamental building blocks of Data Science are Statistics, Machine Learning, Computer Science, Data Analysis, Deep Learning, and Data Visualization. .

Machine Learning 40

Machine Learning Data Science Deep Learning Algorithm 40

Knowledge Hut

NOVEMBER 18, 2023

Companies are actively training machine learning models to search patterns from IoT devices and make forecasts in several fields like: Data quality analysis Behavioral analysis Service quality Edge computing Smart Healthcare Resource consumption Neural networks Attack detection and prediction Distributed deep learning, etc.

Machine Learning 52

Machine Learning Transportation Healthcare Amazon Web Services 52

Knowledge Hut

JUNE 4, 2024

Medical Image Analysis Softengi Another advanced and revolutionizing use case of Data Science in pharmaceutical industry is Medical Image Analysis. With the help of Deep Learning techniques in Data Science, the software can be built to understand and interpret images like X-rays, MRIs, mammograms, etc.

Pharmaceutical 52

Pharmaceutical Data Science Medical Machine Learning 52

Edureka

SEPTEMBER 11, 2023

Generative AI’s magic comes from understanding the intricate structures and patterns in its training data. These algorithms frequently employ methods like Bayesian inference, Markov Chains, and maximum likelihood estimation to create new data. On top of these statistical models, more intricate architectural designs are built.

Algorithm 52

Algorithm Deep Learning Entertainment Healthcare 52

Knowledge Hut

MAY 9, 2024

Skills Required Skills necessary for AI engineers are programming languages, statistics, deep learning, natural language processing, and problem-solving with communication skills. Average Annual Salary of Machine Learning Engineer A machine learning engineer can earn over $132,910 on average per year.

Data Science 52

Data Science Data Architect Data Mining Programming Language 52

Data Engineering Weekly

NOVEMBER 13, 2022

link] Etsy: Deep Learning for Search Ranking at Etsy Etsy writes about its journey from gradient boost decision tree-based search ranking to a neural ranking model. The blog narrates the design of the data collection, modeling & visualization layers.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

ProjectPro

JUNE 9, 2021

Difference between Data Science and Data Engineering Data Science Data Engineering Data Science involves extracting information from raw data to derive business insights and values using statistical methods. Data Engineering is associated with data collecting, processing, analyzing, and cleaning data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

JUNE 20, 2023

Skills A data engineer should have good programming and analytical skills with big data knowledge. A machine learning engineer should know deep learning, scaling on the cloud, working with APIs, etc. Examples Pull daily tweets from the data warehouse hive spreading in multiple clusters.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 27, 2023

Software developers play an important role in data collection and analysis to ensure the company's security. Research and Development Private and government companies in Singapore hire software developers to conduct research and development to create innovative products and improve users' experience.

Medical 98

Medical Programming Language Amazon Web Services Entertainment 98

ProjectPro

JANUARY 31, 2023

There are many reasons why the modern insurance sector prefers machine learning and data science : Rapidly growing data volumes- Consumer electronics with an internet connection, such as smartphones, smart TVs, and fitness trackers, are becoming increasingly popular today.

Insurance 75

Insurance Machine Learning Project Algorithm 75