Pickl AI

JULY 25, 2023

Collaborating with data scientists, to ensure optimal model performance in real-world applications. With expertise in Python, machine learning algorithms, and cloud platforms, machine learning engineers optimize models for efficiency, scalability, and maintenance. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

JULY 18, 2023

While it may not be a traditional programming language, SQL plays a crucial role in Data Science by enabling efficient querying and extraction of data from databases. SQL’s powerful functionalities help in extracting and transforming data from various sources, thus helping in accurate data analysis.

Data Science 52

Data Science SQL Data Scientist Python 52

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? It allows users to work with graph-structured data and offers graph computation and analysis tools.

Hadoop 52

Hadoop Big Data Big Data Clustering 52

Pickl AI

JULY 29, 2024

Machine Learning and Predictive Analytics Hadoop’s distributed processing capabilities make it ideal for training Machine Learning models and running predictive analytics algorithms on large datasets. Software Installation Install the necessary software, including the operating system, Java, and the Hadoop distribution (e.g.,

Hadoop 52

Hadoop Clustering Big Data Big Data 52

Pickl AI

AUGUST 21, 2024

Advanced crawling algorithms allow them to adapt to new content and changes in website structures. Precision: Advanced algorithms ensure they accurately categorise and store data. Scraping: Once the URLs are indexed, a web scraper extracts specific data fields from the relevant pages.

Apache Hadoop 52

Apache Hadoop Hadoop Database Data Quality 52

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 40

Analytics Analytics Big Data Big Data 40

DagsHub

OCTOBER 23, 2024

It allows unstructured data to be moved and processed easily between systems. Kafka is highly scalable and ideal for high-throughput and low-latency data pipeline applications. Apache Hadoop Apache Hadoop is an open-source framework that supports the distributed processing of large datasets across clusters of computers.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

FEBRUARY 23, 2025

Introduction to Big Data Tools In todays data-driven world, organisations are inundated with vast amounts of information generated from various sources, including social media, IoT devices, transactions, and more. Big Data tools are essential for effectively managing and analysing this wealth of information. Use Cases : Yahoo!

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52