Apache Hadoop, Data Analysis and Machine Learning

Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

JANUARY 12, 2023

This covers commercial products from data warehouse and business intelligence providers as well as open-source frameworks like Apache Hadoop, Apache Spark, and Apache Presto. You can perform analytics with Data Lakes without moving your data to a different analytics system. 4.

Data Lakes

Data Lakes Data Warehouse Hadoop Machine Learning

10 Must-Have AI Engineering Skills in 2024

Data Science Dojo

MAY 24, 2024

AI engineering is the discipline that combines the principles of data science, software engineering, and machine learning to build and manage robust AI systems. Machine Learning Algorithms Recent improvements in machine learning algorithms have significantly enhanced their efficiency and accuracy.

Deep Learning

Deep Learning Deep Learning Machine Learning Machine Learning

A Practical Introduction to PySpark

Towards AI

SEPTEMBER 28, 2023

This article explains what PySpark is, some common PySpark functions, and data analysis of the New York City Taxi & Limousine Commission Dataset using PySpark. PySpark is an interface for Apache Spark in Python. It does in-memory computations to analyze data in real-time. What is PySpark?

Apache Hadoop

Apache Hadoop Hadoop Python SQL

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What is Data-driven vs AI-driven Practices?

Pickl AI

JANUARY 12, 2025

Introduction Are you struggling to decide between data-driven practices and AI-driven strategies for your business? Besides, there is a balance between the precision of traditional data analysis and the innovative potential of explainable artificial intelligence. AI-Driven Uncovering complex patterns in large datasets.

Artificial Intelligence

Artificial Intelligence Artificial Intelligence AI AI

How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

OCTOBER 23, 2024

Unstructured data makes up 80% of the world's data and is growing. Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging.

Machine Learning

Machine Learning Machine Learning Data Lakes AI

Navigating the Big Data Frontier: A Guide to Efficient Handling

Women in Big Data

OCTOBER 9, 2024

Big data management involves a series of processes, including collecting, cleaning, and standardizing data for analysis, while continuously accommodating new data streams. These procedures are central to effective data management and crucial for deploying machine learning models and making data-driven decisions.

Big Data

Big Data Big Data Apache Kafka Data Pipeline

Data Science Career FAQs Answered: Educational Background

Mlearning.ai

MAY 23, 2023

A fair understanding of calculus, linear algebra, probability, and statistics is essential for tasks such as modeling, analysis, and inference. These languages are used for data manipulation, analysis, and building machine learning models. Education: Bachelors in Computer Scene or a Quantitative field.

Data Science

Data Science Data Scientist Machine Learning Machine Learning

The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

JULY 25, 2023

Proficient in programming languages like Python or R, data manipulation libraries like Pandas, and machine learning frameworks like TensorFlow and Scikit-learn, data scientists uncover patterns and trends through statistical analysis and data visualization. Big Data Technologies: Hadoop, Spark, etc.

Data Engineering

Data Engineering Data Engineering Data Engineer Data Engineering

Introduction to R Programming For Data Science

Pickl AI

JULY 10, 2023

As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. The programming language can handle Big Data and perform effective data analysis and statistical modelling. R is a popular programming language and environment widely used in the field of data science.

Data Science

Data Science Data Scientist Machine Learning Machine Learning

Spark Vs. Hadoop – All You Need to Know

Pickl AI

SEPTEMBER 19, 2024

Hadoop, focusing on their strengths, weaknesses, and use cases. You’ll better understand which framework best suits different data processing needs and business scenarios by the end. What is Apache Hadoop? This component bridges the gap between traditional SQL databases and big data processing.

Hadoop

Hadoop Big Data Big Data Clustering

A Comprehensive Guide to the main components of Big Data

Pickl AI

DECEMBER 2, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. It is known for its high fault tolerance and scalability.

Big Data

Big Data Big Data Data Lakes Apache Hadoop

8 Best Programming Language for Data Science

Pickl AI

JULY 18, 2023

However, with libraries like NumPy, Pandas, and Matplotlib, Python offers robust tools for data manipulation, analysis, and visualization. Additionally, its natural language processing capabilities and Machine Learning frameworks like TensorFlow and scikit-learn make Python an all-in-one language for Data Science.

Data Science

Data Science SQL Data Scientist Python

How LotteON built a personalized recommendation system using Amazon SageMaker and MLOps

AWS Machine Learning Blog

MAY 16, 2024

In this post, we share how LotteON improved their recommendation service using Amazon SageMaker and machine learning operations (MLOps). With Amazon EMR, which provides fully managed environments like Apache Hadoop and Spark, we were able to process data faster.

AWS

AWS ML ML Deep Learning

Discover the Most Important Fundamentals of Data Engineering

Pickl AI

NOVEMBER 4, 2024

Data Engineering emphasises the infrastructure and tools necessary for data collection, storage, and processing, while Data Engineers concentrate on the architecture, pipelines, and workflows that facilitate data access. Key components of data warehousing include: ETL Processes: ETL stands for Extract, Transform, Load.

Data Engineering

Data Engineering Data Engineering Data Engineer Data Engineering

10 Best Data Engineering Books [Beginners to Advanced]

Pickl AI

AUGUST 1, 2023

Data Pipeline Orchestration: Managing the end-to-end data flow from data sources to the destination systems, often using tools like Apache Airflow, Apache NiFi, or other workflow management systems. It teaches Pandas, a crucial library for data preprocessing and transformation.

Data Engineering

Data Engineering Data Engineering Data Engineer Data Engineering

A Comprehensive Guide to the Main Components of Big Data

Pickl AI

NOVEMBER 25, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. It is known for its high fault tolerance and scalability.

Big Data

Big Data Big Data Data Lakes Apache Hadoop

Big Data as a Service (BDaaS): A Comprehensive Overview

Pickl AI

SEPTEMBER 11, 2024

Platform as a Service (PaaS) PaaS offerings provide a development environment for building, testing, and deploying Big Data applications. This layer includes tools and frameworks for data processing, such as Apache Hadoop, Apache Spark, and data integration tools.

Big Data

Big Data Big Data Big Data Analytics Big Data Analytics

What is a Hadoop Cluster?

Pickl AI

JULY 29, 2024

Log Analysis These are well-suited for analysing log data from various sources, such as web servers, application logs, and sensor data, to gain insights into user behaviour and system performance. Software Installation Install the necessary software, including the operating system, Java, and the Hadoop distribution (e.g.,

Hadoop

Hadoop Clustering Big Data Big Data

Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

JULY 20, 2023

Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes. Techniques like regression analysis, time series forecasting, and machine learning algorithms are used to predict customer behavior, sales trends, equipment failure, and more.

Analytics

Analytics Analytics Big Data Big Data

Web Scraping vs. Web Crawling: Understanding the Differences

Pickl AI

AUGUST 21, 2024

Scraping: Once the URLs are indexed, a web scraper extracts specific data fields from the relevant pages. This targeted extraction focuses on the information needed for analysis. Data Analysis: The extracted data is then structured and analysed for insights or used in applications.

Apache Hadoop

Apache Hadoop Hadoop Database Data Quality

Top Big Data Tools Every Data Professional Should Know

Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. Machine Learning Integration : Built-in ML capabilities streamline model development and deployment.

Big Data

Big Data Big Data Apache Hadoop Apache Kafka

Data Science Current

Data lakes vs. data warehouses: Decoding the data storage debate

10 Must-Have AI Engineering Skills in 2024

Webinars

Trending Sources

A Practical Introduction to PySpark

Webinars

What is Data-driven vs AI-driven Practices?

How to Manage Unstructured Data in AI and Machine Learning Projects

Navigating the Big Data Frontier: A Guide to Efficient Handling

Data Science Career FAQs Answered: Educational Background

The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Introduction to R Programming For Data Science

Spark Vs. Hadoop – All You Need to Know

A Comprehensive Guide to the main components of Big Data

8 Best Programming Language for Data Science

How LotteON built a personalized recommendation system using Amazon SageMaker and MLOps

Discover the Most Important Fundamentals of Data Engineering

10 Best Data Engineering Books [Beginners to Advanced]

A Comprehensive Guide to the Main Components of Big Data

Big Data as a Service (BDaaS): A Comprehensive Overview

What is a Hadoop Cluster?

Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Web Scraping vs. Web Crawling: Understanding the Differences

Top Big Data Tools Every Data Professional Should Know

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