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The 6 best ChatGPT plugins for data science 

Data Science Dojo

This means that you can use natural language prompts to perform advanced data analysis tasks, generate visualizations, and train machine learning models without the need for complex coding knowledge. This can be useful for data scientists who need to streamline their data science pipeline or automate repetitive tasks.

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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

These tools will help make your initial data exploration process easy. ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. This tool automatically detects problems in an ML dataset.

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Harness the power of AI and ML using Splunk and Amazon SageMaker Canvas

AWS Machine Learning Blog

Instead, organizations are increasingly looking to take advantage of transformative technologies like machine learning (ML) and artificial intelligence (AI) to deliver innovative products, improve outcomes, and gain operational efficiencies at scale. To facilitate this, an automated data engineering pipeline is built using AWS Step Functions.

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

Pickl AI

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Read more to know. Cloud Platforms: AWS, Azure, Google Cloud, etc.

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AI in Time Series Forecasting

Pickl AI

Summary: AI in Time Series Forecasting revolutionizes predictive analytics by leveraging advanced algorithms to identify patterns and trends in temporal data. By automating complex forecasting processes, AI significantly improves accuracy and efficiency in various applications. billion by 2030. What is Time Series Forecasting?

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Generative AI in Software Development

Mlearning.ai

Increase your productivity in software development with Generative AI As I mentioned in Generative AI use case article, we are seeing AI-assisted developers. Overall Generative AI in SDLC Here is how Generative AI can help in SDLC stages (we may see more use cases as Generative AI matures).

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Big Data vs. Data Science: Demystifying the Buzzwords

Pickl AI

This crucial step involves handling missing values, correcting errors (addressing Veracity issues from Big Data), transforming data into a usable format, and structuring it for analysis. This often takes up a significant chunk of a data scientist’s time. Think graphs, charts, and summary statistics.