O'Reilly Media

SEPTEMBER 19, 2023

” Consider the structural evolutions of that theme: Stage 1: Hadoop and Big Data By 2008, many companies found themselves at the intersection of “a steep increase in online activity” and “a sharp decline in costs for storage and computing.” And Hadoop rolled in. Goodbye, Hadoop. And it was good.

Hadoop 135

Hadoop Algorithm ML ML 135

Data Science Dojo

MAY 24, 2024

They work at the intersection of various technical domains, requiring a blend of skills to handle data processing, algorithm development, system design, and implementation. Machine Learning Algorithms Recent improvements in machine learning algorithms have significantly enhanced their efficiency and accuracy.

Deep Learning 195

Deep Learning Deep Learning Machine Learning Machine Learning 195

Data Science Dojo

AUGUST 27, 2024

Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Hadoop and Spark: These are like powerful computers that can process huge amounts of data quickly. Normalization: Making data consistent and comparable.

Data Scientist 195

Data Scientist Data Science Machine Learning Machine Learning 195

Data Science Dojo

JULY 7, 2023

Data Science intertwines statistics, problem-solving, and programming to extract valuable insights from vast data sets. This discipline takes raw data, deciphers it, and turns it into a digestible format using various tools and algorithms. Tools such as Python, R, and SQL help to manipulate and analyze data.

Data Science 195

Data Science Data Scientist Python Decision Trees 195

Data Science Dojo

AUGUST 30, 2023

It directly focuses on implementing scientific methods and algorithms to solve real-world business problems and is a key player in transforming raw data into significant and actionable business insights. Machine learning algorithms Machine learning forms the core of Applied Data Science.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195

How to Learn Machine Learning

APRIL 26, 2025

The responsibilities of this phase can be handled with traditional databases (MySQL, PostgreSQL), cloud storage (AWS S3, Google Cloud Storage), and big data frameworks (Hadoop, Apache Spark). such data resources are cleaned, transformed, and analyzed by using tools like Python, R, SQL, and big data technologies such as Hadoop and Spark.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Pickl AI

APRIL 21, 2025

Data Science, on the other hand, uses scientific methods and algorithms to analyses this data, extract insights, and inform decisions. Big Data technologies include Hadoop, Spark, and NoSQL databases. Machine Learning: Understanding and applying various algorithms. Together, they power data-driven innovation across industries.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Smart Data Collective

SEPTEMBER 24, 2020

The biggest breakthroughs in machine learning have only emerged over the last five years, as new advances in Hadoop and other big data technology make artificial intelligence algorithms more practical. Google Photos used complex machine learning algorithms to solve this challenge. Computational photography is a prime example.

Machine Learning 145

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 145

Pickl AI

DECEMBER 25, 2024

Machine learning algorithms play a central role in building predictive models and enabling systems to learn from data. Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently. Their role demands proficiency in handling large datasets, developing algorithms, and implementing AI solutions.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Data Science Dojo

JULY 24, 2023

Different algorithms and techniques are employed to achieve eventual consistency. Hadoop Distributed File System (HDFS) : HDFS is a distributed file system designed to store vast amounts of data across multiple nodes in a Hadoop cluster. They use redundancy and replication to ensure data availability.

Big Data 195

Big Data Big Data Data Engineering Data Engineer 195

Pickl AI

JANUARY 12, 2025

A generative AI company exemplifies this by offering solutions that enable businesses to streamline operations, personalise customer experiences, and optimise workflows through advanced algorithms. Data forms the backbone of AI systems, feeding into the core input for machine learning algorithms to generate their predictions and insights.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

Smart Data Collective

AUGUST 26, 2021

Hadoop has also helped considerably with weather forecasting. Instead, it uses AI-powered algorithms to process weather data and generates real-time weather forecasts. That means you can now learn about the weather conditions at precise locations, such as residential buildings, airports, farms, construction sites, etc.

Analytics 133

Analytics Analytics Big Data Analytics Big Data Analytics 133

ODSC - Open Data Science

APRIL 28, 2023

Furthermore, data enrichment can help ensure that AI algorithms are trained on diverse data, reducing the risk of bias. Adding datasets for underrepresented groups can help ensure that AI algorithms are not perpetuating any preexisting biases.

ML 98

ML ML Data Silos Data Quality 98

Analytics Vidhya

APRIL 25, 2023

Introduction Since India gained independence, we have always emphasized the importance of elections to make decisions. Seventeen Lok Sabha Elections and over four hundred state legislative assembly elections have been held in India. Earlier, political campaigns used to be conducted through rallies, public speeches, and door-to-door canvassing.

AI 306

AI AI Analytics Analytics 306

ODSC - Open Data Science

MAY 31, 2023

Commonly used technologies for data storage are the Hadoop Distributed File System (HDFS), Amazon S3, Google Cloud Storage (GCS), or Azure Blob Storage, as well as tools like Apache Hive, Apache Spark, and TensorFlow for data processing and analytics.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131

Pickl AI

OCTOBER 27, 2024

Enrolling in a Data Science course keeps you updated on the latest advancements, such as machine learning algorithms and data visualisation techniques. Big Data Technologies: Familiarity with tools like Hadoop and Spark is increasingly important. This continuous learning environment fosters professional growth and adaptability.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

Mathematics is critical in Data Analysis and algorithm development, allowing you to derive meaningful insights from data. Linear algebra is vital for understanding Machine Learning algorithms and data manipulation. Scikit-learn covers various classification , regression , clustering , and dimensionality reduction algorithms.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

IBM Journey to AI blog

MARCH 21, 2024

GPUs (graphics processing units) and TPUs (tensor processing units) are specifically designed to handle complex mathematical computations central to AI algorithms, offering significant speedups compared with traditional CPUs. Additionally, using in-memory databases and caching mechanisms minimizes latency and improves data access speeds.

Apache Hadoop 79

Apache Hadoop AI AI Natural Language Processing 79

Pickl AI

DECEMBER 9, 2024

Familiarise yourself with essential tools like Hadoop and Spark. What are the Main Components of Hadoop? Hadoop consists of the Hadoop Distributed File System (HDFS) for storage and MapReduce for processing data across distributed systems. What is the Role of a NameNode in Hadoop ? What is a DataNode in Hadoop?

Big Data 52

Big Data Big Data Hadoop Apache Kafka 52

Data Science 101

JUNE 10, 2019

Data scientists are the bridge between programming and algorithmic thinking. The power of data science comes from a deep understanding of statistics,algorithms, programming, and communication skills. Hadoop, SQL, Python, R, Excel are some of the tools you’ll need to be familiar using. Data Scientists.

Data Science 96

Data Science Data Scientist Data Analyst Data Engineering 96

AWS Machine Learning Blog

MAY 16, 2024

Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

AWS 126

AWS ML ML Deep Learning 126

Smart Data Collective

SEPTEMBER 13, 2020

These Hadoop based tools archive links and keep track of them. They use a sophisticated data-driven algorithm to assess the quality of these sites based on the volume and quantity of inbound links. This algorithm is known as Google PageRank. Search engines use data mining tools to find links from other sites.

Analytics 121

Analytics Analytics Big Data Big Data 121

Smart Data Collective

JUNE 3, 2019

Although some banks are already developing pilots with Hadoop and other associated technologies, there is still a long way to go. Variables Financial Industry Uses in its Big Data Algorithms. Here are some factors that financial industry big data algorithms rely on. Big data algorithms rely heavily on credit score data.

Big Data 85

Big Data Big Data Data Silos AI 85

Dataconomy

JULY 24, 2023

Concepts such as linear algebra, calculus, probability, and statistical theory are the backbone of many data science algorithms and techniques. Coding skills are essential for tasks such as data cleaning, analysis, visualization, and implementing machine learning algorithms. Specializing can make you stand out from other candidates.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

IBM Journey to AI blog

SEPTEMBER 19, 2023

Many functions of data analytics—such as making predictions—are built on machine learning algorithms and models that are developed by data scientists. And you should have experience working with big data platforms such as Hadoop or Apache Spark. Those who work in the field of data science are known as data scientists.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

ODSC - Open Data Science

DECEMBER 19, 2023

They use their knowledge of machine learning algorithms, programming languages, and data science tools to build models that can be used to automate tasks and make predictions. Machine learning algorithms are a set of mathematical equations that are used to learn from data.

Data Scientist 96

Data Scientist Machine Learning Machine Learning Computer Science 96

Smart Data Collective

JUNE 18, 2019

There are a number of reasons that machine learning, data analytics and Hadoop technology are changing SEO: Machine learning is becoming more widely used in search engine algorithms. SEOs that use machine learning can partially reverse engineer these algorithms.

Big Data 85

Big Data Big Data Machine Learning Machine Learning 85

Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Pickl AI

SEPTEMBER 24, 2024

This data is processed using advanced algorithms to derive insights that inform decision-making.The core of Uber’s strategy revolves around understanding supply and demand dynamics in real time. Machine Learning Algorithms : Uber uses Machine Learning to refine its algorithms continuously.

Analytics 52

Analytics Analytics Machine Learning Machine Learning 52

Smart Data Collective

OCTOBER 28, 2019

A lot of applications can rely on AI algorithms to ensure the best user experience, minimize downtime and keep the programs running smoothly. Hadoop data mining tools have made these monitoring tools more reliable over the last few years. Tech Beacon wrote some very insightful guidelines for people trying to develop applications.

Big Data 85

Big Data Big Data Data Mining Data Mining 85

Pickl AI

JANUARY 13, 2025

Machine Learning Engineer Machine Learning Engineers develop algorithms and models that enable machines to learn from data. Strong understanding of data preprocessing and algorithm development. They explore new algorithms and techniques to improve machine learning models. Strong knowledge of AI algorithms and architectures.

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. For example, financial institutions utilise high-frequency trading algorithms that analyse market data in milliseconds to make investment decisions. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. For example, financial institutions utilise high-frequency trading algorithms that analyse market data in milliseconds to make investment decisions. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Dataconomy

JULY 25, 2023

data visualization tools, machine learning algorithms, and statistical models to uncover valuable information hidden within data. Finance: In the financial sector, data science is used for fraud detection, risk assessment, algorithmic trading, and personalized financial advice.

Data Science 91

Data Science Data Scientist Machine Learning Machine Learning 91

AWS Machine Learning Blog

FEBRUARY 13, 2024

The BigBasket team was running open source, in-house ML algorithms for computer vision object recognition to power AI-enabled checkout at their Fresho (physical) stores. Model training was accelerated by 50% through the use of the SMDDP library, which includes optimized communication algorithms designed specifically for AWS infrastructure.

AWS 131

AWS AI AI ML 131

Smart Data Collective

MAY 8, 2022

Above all, there needs to be a set methodology for data mining, collection, and structure within the organization before data is run through a deep learning algorithm or machine learning. With the evolution of technology and the introduction of Hadoop, Big Data analytics have become more accessible.

Big Data Analytics 122

Big Data Analytics Big Data Analytics Big Data Big Data 122