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

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

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

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. Key Skills Experience with cloud platforms (AWS, Azure).

AI 52

AI AI Machine Learning Machine Learning 52

Smart Data Collective

NOVEMBER 8, 2020

This will enable you to leverage the right algorithms to create good, well structured, and performing software. Spark outperforms old parallel systems such as Hadoop, as it is written using Scala and helps interface with other programming languages and other tools such as Dask. Data processing is often done in batches.

Data Engineering 104

Data Engineering Data Engineering Data Engineering Data Engineer 104

Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Understanding Machine Learning algorithms and effective data handling are also critical for success in the field. Below, we explore some of the most widely used algorithms in ML.

Machine Learning 52

Machine Learning Machine Learning ML ML 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

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Big Data Technologies: Hadoop, Spark, etc. Big Data Processing: Apache Hadoop, Apache Spark, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Mlearning.ai

MAY 23, 2023

Check out this course to build your skillset in Seaborn —  [link] Big Data Technologies Familiarity with big data technologies like Apache Hadoop, Apache Spark, or distributed computing frameworks is becoming increasingly important as the volume and complexity of data continue to grow.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Mlearning.ai

JANUARY 28, 2023

TensorFlow: TensorFlow is an open source library for building neural networks and other deep learning algorithms on top of GPUs. Spark: Spark is a popular platform used for big data processing in the Hadoop ecosystem. Using a cloud provider such as Google Cloud Platform, Amazon AWS, Azure Cloud, or IBM SoftLayer 2.

Machine Learning 52

Machine Learning Machine Learning Data Science ML 52

Pickl AI

DECEMBER 4, 2024

The field has evolved significantly from traditional statistical analysis to include sophisticated Machine Learning algorithms and Big Data technologies. Issues such as algorithmic bias, data privacy, and transparency are becoming critical topics of discussion within the industry.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

The MLOps Blog

MAY 31, 2023

From an algorithmic perspective, Learning To Rank (LeToR) and Elastic Search are some of the most popular algorithms used to build a Seach system. We can collect and use user-product historical interaction data to train recommendation system algorithms. are some examples. Let’s understand this with an example.

ML 59

ML ML Algorithm Machine Learning 59

ODSC - Open Data Science

JANUARY 7, 2025

Just as a writer needs to know core skills like sentence structure and grammar, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and soon. Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

APRIL 2, 2024

Predictive Analytics: Forecasting future outcomes based on historical data and statistical algorithms. Hadoop/Spark: Frameworks for distributed storage and processing of big data. Cloud Platforms (AWS, Azure, Google Cloud): Infrastructure for scalable and cost-effective data storage and analysis.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

DagsHub

OCTOBER 23, 2024

Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop. Apache Hadoop Apache Hadoop is an open-source framework that supports the distributed processing of large datasets across clusters of computers. Data Processing Tools These tools are essential for handling large volumes of unstructured data.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

DagsHub

NOVEMBER 11, 2024

We use data-specific preprocessing and ML algorithms suited to each modality to filter out noise and inconsistencies in unstructured data. Additionally, context-aware algorithms enhance data quality by interpreting information based on its surrounding context, improving relevance for specific tasks. Tools like Unstructured.io

AI 52

AI AI Data Lakes Database 52

Heartbeat

JULY 31, 2023

It uses state-of-the-art algorithms such as Bayesian optimization and grid search to automatically search through the hyperparameter space and find the best ones for the given machine learning problem. Comet also integrates with popular data storage and processing tools like Amazon S3, Google Cloud Storage, and Hadoop.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52