How to Learn Machine Learning

APRIL 26, 2025

Data Storage and Management Once data have been collected from the sources, they must be secured and made accessible. 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).

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ODSC - Open Data Science

FEBRUARY 2, 2023

Analytics and Data Analysis Coming in as the 4th most sought-after skill is data analytics, as many data scientists will be expected to do some analysis in their careers. This doesn’t mean anything too complicated, but could range from basic Excel work to more advanced reporting to be used for data visualization later on.

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phData

MAY 25, 2023

Two of the platforms that we see emerging as a popular combination of data warehousing and business intelligence are the Snowflake Data Cloud and Power BI. Debuting in 2015, Power BI has undergone meaningful updates that have made it a leader not just in data visualization, but in the business intelligence space as well.

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Data Science Dojo

MAY 24, 2024

Navigate through 6 Popular Python Libraries for Data Science R R is another important language, particularly valued in statistics and data analysis, making it useful for AI applications that require intensive data processing.

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DrivenData Labs

NOVEMBER 14, 2023

If you are unsure whether a specific dataset meets the competition data requirement, just ask in the competition forum. HRRR has been used for applications like predicting the path of wildfire smoke and optimizing wind energy use. SMAP has been used for projects like monitoring drought in the midwestern United States.

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Mlearning.ai

MAY 23, 2023

A good course to upskill in this area is — Machine Learning Specialization Data Visualization The ability to effectively communicate insights through data visualization is important. Check out this course to upskill on Apache Spark —  [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus.

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ODSC - Open Data Science

APRIL 3, 2023

As you’ll see below, however, a growing number of data analytics platforms, skills, and frameworks have altered the traditional view of what a data analyst is. Data Presentation: Communication Skills, Data Visualization Any good data analyst can go beyond just number crunching.

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Pickl AI

DECEMBER 25, 2024

They need to translate data insights into actionable business strategies, making stakeholder engagement and storytelling through data visualization critical skills. Data Scientists rely on technical proficiency. They must also stay updated on tools such as TensorFlow, Hadoop, and cloud-based platforms like AWS or Azure.

Data Science 52

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Pickl AI

JANUARY 13, 2025

They employ statistical methods and machine learning techniques to interpret data. Key Skills Expertise in statistical analysis and data visualization tools. Key Skills Experience with cloud platforms (AWS, Azure). Data Analyst Data Analysts gather and interpret data to help organisations make informed decisions.

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Cambridge Intelligence

OCTOBER 19, 2023

That’s why our data visualization SDKs are database agnostic: so you’re free to choose the right stack for your application. Part of AWS – with high availability worldwide and easy integration with the rest of AWS’ products.

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Women in Big Data

DECEMBER 9, 2024

It integrates seamlessly with a wide range of data sources like Excel, Azure and SQL server, Salesforce, SAP Hana, IBM Netezza and CDP which makes it a compelling choice for businesses that have already invested in the Microsoft ecosystem. It allows users to create highly customizable and visually appealing reports.

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ODSC - Open Data Science

FEBRUARY 6, 2024

Cloud-Based Orchestration Tools While open-source tools are powerful, cloud-based orchestration services like AWS Glue, Azure Data Factory, and Google Cloud Dataflow offer managed solutions that reduce the burden of infrastructure management.

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IBM Journey to AI blog

FEBRUARY 15, 2024

However, using the right frameworks and tools can simplify the process and improve overall data visualization and transparency. Implementing and maintaining Kubernetes observability is a large, complex undertaking. Integrated solutions, like OpenTelemetry, can manage all three major observability practices.

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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. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

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Mlearning.ai

MARCH 15, 2023

Responsibilities of a Data Analyst Data analysts, on the other hand, help businesses and organizations make data-driven decisions through their analytical skills. Their job is mainly to collect, process, analyze, and create detailed reports on data to meet business needs.

Data Science 52

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Mlearning.ai

JANUARY 26, 2023

Presenters and participants had the opportunity to hear about and evaluate the pros and cons of different back end technologies and data formats for different uses such as web-mapping, data visualization, and the sharing of meta-data. Data, 4(3), 92. BUILDING EARTH OBSERVATION DATA CUBES ON AWS.

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Pickl AI

JULY 30, 2024

It is useful for visualising complex data and identifying patterns and trends. Some of the key platforms used for cloud computing include: AWS (Amazon Web Services) AWS is a cloud computing platform that provides a range of services, including storage, computing, and analytics.

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The MLOps Blog

MARCH 20, 2023

Data Backup and Recovery : Have a data storage platform that supports a contingency plan for unexpected data loss and deletion, which can be quite common in a long-duration project. Data Compression : Explore data compression techniques to optimize storage space, primarily as long-term ML projects collect more data.

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Pickl AI

DECEMBER 4, 2024

Understanding real-time data processing frameworks, such as Apache Kafka, will also enhance your ability to handle dynamic analytics. Master Data Visualization Techniques Data visualization is key to effectively communicating insights. Additionally, familiarity with cloud platforms (e.g.,

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ODSC - Open Data Science

JANUARY 7, 2025

Environments Data science environments encompass the tools and platforms where professionals perform their work. From development environments like Jupyter Notebooks to robust cloud-hosted solutions such as AWS SageMaker, proficiency in these systems is critical.

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Pickl AI

APRIL 2, 2024

Tableau/Power BI: Visualization tools for creating interactive and informative data visualizations. 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

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ODSC - Open Data Science

JANUARY 29, 2024

Data science methodologies and skills can be leveraged to design these experiments, analyze results, and iteratively improve prompt strategies. Using skills such as statistical analysis and data visualization techniques, prompt engineers can assess the effectiveness of different prompts and understand patterns in the responses.

Data Science 52

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Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

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Heartbeat

JULY 31, 2023

Comet also works with popular cloud platforms like AWS, GCP, and Azure, making it easy to deploy models to the cloud with just a few clicks. In addition, Comet offers integrations with popular communication tools like Slack, making it easy to share experiment results and collaborate with team members.

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phData

JULY 18, 2023

Learn how to use dbt with Snowflake Data Applications and ML/AI After the data has been successfully replicated, transformed and validated, the next step is to leverage it to extract meaningful insights. Snowflake allows its users to interface with the software without worrying about the infrastructure it runs or how to install it.

Data Warehouse 52

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Dataconomy

APRIL 25, 2023

AI tools can help you with various aspects of presentation design, such as content generation, slide layout, data visualization, speech synthesis, and more. Azure AI enables businesses to build, deploy, and manage AI applications at scale, using pre-built models or custom ones. It is one of the best AI tools for business.

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How to Learn Machine Learning

MAY 3, 2025

All the clouds are different, and for us GCP offers some cool benefits that we will highlight in this article vs the AWS AI Services or Azure Machine Learning. Sit back, relax, and enjoy this comprehensive guide to GCP AI Platform your ticket to leveraging cutting-edge artificial intelligence in the cloud.

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Pickl AI

MARCH 19, 2025

Apache Airflow Apache Airflow is a workflow automation tool that allows data engineers to schedule, monitor, and manage data pipelines efficiently. It helps streamline data processing tasks and ensures reliable execution. It helps organisations understand their data better and make informed decisions.

Data Engineering 52

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