AltexSoft

NOVEMBER 17, 2021

Digitizing medical reports and other records is one of the critical tasks for medical institutions to optimize their document flow. But some healthcare organizations like FDA implement various document classification techniques to process tons of medical archives daily. An example of document structure in healthcare insurance.

Machine Learning 75

Machine Learning Insurance Medical Healthcare 75

Knowledge Hut

DECEMBER 29, 2023

Learning Outcomes: Acquire the skills necessary to assess models developed from data. Apply the algorithms to a real-world situation, optimize the models learned, and report on the predicted accuracy that can be reached using the models. Analyze voluminous text data created by a variety of practical applications.

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.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

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

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Towards Data Science

OCTOBER 15, 2024

A quick recap of part i The evolution of a data pipeline In part I , we watched SmartGym grow into (version 2.1), an integrated health and fitness platform that streams , processes , and saves data from a range of gym equipment sensors and medical devices. With only one data source, consistency is implied.

Architecture 75

Architecture Data Database Systems 75

AltexSoft

DECEMBER 15, 2021

On the surface, ML algorithms take the data, develop their own understanding of it, and generate valuable business insights and predictions — all without human intervention. It boosts the performance of ML specialists relieving them of repetitive tasks and enables even non-experts to experiment with smart algorithms.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

ProjectPro

FEBRUARY 25, 2022

Evolution of Machine Learning Applications in Finance : From Theory to Practice Here are some significant advantages of implementing a data pipeline in machine learning- Efficient Scheduling and Runtime As the machine learning process evolves, you need to repeat many aspects of the machine learning pipeline throughout the organization.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

RandomTrees

DECEMBER 20, 2023

Modern medical professionals and institutions use Edge AI for surgical procedures. Moreover, it allows patients to monitor their activities and perform remote surgeries. Most of today’s edge AI algorithms perform local inference directly on data that the device sees directly.

IT 52

IT Hospitality Healthcare Deep Learning 52

ProjectPro

FEBRUARY 8, 2016

The main techniques used here are data mining and data aggregation. Descriptive analytics involves using descriptive statistics such as arithmetic operations on existing data. These operations make raw data understandable to investors, shareholders, and managers.

Data Mining 56

Data Mining Big Data Medical Data Analytics 56

Edureka

JULY 4, 2024

Recommendation systems: Spotify, Amazon, and Netflix use recommendation algorithms to reach audiences. After learning the user’s tastes, these algorithms recommend media, items, and music. Siri, email screening, and Netflix recommendation algorithms are examples. This method filters trash emails and categorizes them.

Medical 40

Medical Algorithm Datasets Healthcare 40

U-Next

AUGUST 18, 2022

Data Science may combine arithmetic, business savvy, technologies, algorithm, and pattern recognition approaches. These factors all work together to help us uncover underlying patterns or observations in raw data that can be extremely useful when making important business choices. Theaters, channels, etc.,

Unstructured Data 40

Unstructured Data Data Science Medical Business Intelligence 40

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. To build such ML projects, you must know different approaches to cleaning raw data. To develop such algorithms, you need to have a thorough understanding of the following: a.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

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.

Data Science 40

Data Science Deep Learning Machine Learning NoSQL 40

U-Next

MARCH 14, 2023

Introduction Explainable Artificial Intelligence (XAI) is a set of procedures and strategies that enables the output and consequences of Machine Learning algorithms to be understood and trusted by people. Humans find it difficult to understand and trace the steps taken by the algorithm as AI develops.

Machine Learning 40

Machine Learning Algorithm Datasets Utilities 40

Knowledge Hut

NOVEMBER 2, 2023

Image Recognition: Machine learning models can be specifically programmed to identify or categorize photos, thus opening doors to a wide range of tasks such as object detection, facial recognition, medical image analysis, and more. AI systems can minutely analyze existing compositions and generate new musical pieces based on learned patterns.

Machine Learning 52

Machine Learning Deep Learning Utilities Medical 52

ProjectPro

OCTOBER 27, 2021

The huge volumes of financial data have helped the finance industry streamline processes, reduce investment risks, and optimize investment portfolios for clients and companies. There is a wide range of open-source machine learning algorithms and tools that fit exceptionally with financial data. Our data is imbalanced.

Finance 52

Finance Machine Learning Project Banking 52

Knowledge Hut

APRIL 23, 2024

Big Data Use Cases in Industries You can go through this section and explore big data applications across multiple industries. Clinical Decision Support: By analyzing vast amounts of patient data and offering in-the-moment insights and suggestions, use cases for big data in healthcare helps workers make well-informed judgments.

Big Data 52

Big Data Recruitment Retail Transportation 52

U-Next

SEPTEMBER 23, 2022

It offers data that makes it easier to comprehend how the company is doing on a global scale. Additionally, it is crucial to present the various stakeholders with the current raw data. Drill-down, data mining, and other techniques are used to find the underlying cause of occurrences. Diagnostic Analytics.

Data Mining 40

Data Mining Business Analyst Deep Learning Algorithm 40

Edureka

APRIL 17, 2023

What is the Role of Data Analytics? Data analytics is used to make sense of data and provide valuable insights to help organizations make better decisions. Data analytics aims to turn raw data into meaningful insights that can be used to solve complex problems.

Portfolio 40

Portfolio Data Analytics Project Data Mining 40

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

JULY 26, 2021

Deep Learning in Medical Imaging using TensorFlow 5. Gatys’ paper, “A Neural Algorithm of Artistic Style,” neural style transfer has taken the world by storm and has caught the attention of many. One possible way of achieving this is training a CNN with the MFCC spectrograms obtained from the raw data.

Project 40

Project Deep Learning Medical Datasets 40

ProjectPro

NOVEMBER 14, 2015

Hadoop can be used to carry out data processing using either the traditional (map/reduce) or Spark-based (providing an interactive platform to process queries in real-time) approach. Given a graphical relation between variables, an algorithm needs to be developed which predicts which two nodes are most likely to be connected?

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

AUGUST 16, 2021

FAQs on Machine Learning Projects for Resume Machine Learning Projects for Resume - A Must-Have to Get Hired in 2021 Machine Learning and Data Science have been on the rise in the latter part of the last decade. Quite similar to classification is clustering but with the minor difference of working with unlabelled data.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

Edureka

MARCH 26, 2025

Multiple levels: Raw data is accepted by the input layer. What follows is a list of what each neuron does: Input Reception: Neurons receive inputs from other neurons or raw data. There is a distinct function for each layer in the processing of data: Input Layer: The first layer of the network.

Raw Data 40

Raw Data Architecture Deep Learning Finance 40

AltexSoft

OCTOBER 22, 2021

Deep learning is a subfield of machine learning where artificial neural networks — complex algorithms modeled to work in a way similar to human brains — learn from large sets of data. Artificial intelligence (AI) is simply any computer algorithm that remotely resembles human problem-solving. What is deep learning?

Deep Learning 52

Deep Learning Algorithm Machine Learning Raw Data 52

ProjectPro

JANUARY 17, 2022

The algorithms are designed to classify the given data points into n number of different classes based on patterns observed within the data. Multi Class Classification Models and Algorithms 1. Medical Diagnosis - The process of diagnosing whether the patient has a given disease and its severity is a multiclass problem.

Python 52

Python Algorithm Machine Learning Datasets 52

Knowledge Hut

OCTOBER 27, 2023

Weather Tracker The weather tracker project involves visualizing historical weather data to provide insights into temperature trends, precipitation, and weather conditions. Weather data is abundant, and it offers unique variations and patterns. Grab info from a website using good APIs. Look for patterns in temperature.

BI 52

BI Project Datasets Healthcare 52

ProjectPro

FEBRUARY 19, 2021

Regression Analysis: Understanding the Related Terminology But before we go any further, let’s look at some of the most common terminologies associated with regression analysis that will come up: Outliers : Outliers are basically values or data points that are very stray from the general population or distribution of data.

Machine Learning 40

Machine Learning Algorithm Datasets Data Science 40

U-Next

SEPTEMBER 29, 2022

Data from IoT sensors, text, speech, and vision are all included. A medical diagnosis can benefit greatly from multimodal approaches, including optical character recognition and machine vision. . Since personal and private data is used to make essential decisions, the GDPR and CCPA regulations ensure AI transparency.

Medical 40

Medical Machine Learning Manufacturing Raw Data 40

Edureka

APRIL 1, 2025

Synthetic data : This means that researchers and developers use fake data to try and improve their algorithms. This way, they don’t put real data at risk regarding privacy or security. Why is data augmentation important? Data augmentation improves machine learning models by making the most of available data.

Datasets 40

Datasets Machine Learning Deep Learning Data 40