Becoming Human

MAY 15, 2023

These communities will help you to be updated in the field, because there are some experienced data scientists posting the stuff, or you can talk with them so they will also guide you in your journey. Data Analysis After learning math now, you are able to talk with your data.

Data Science 75

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Pickl AI

MARCH 4, 2024

With its intuitive interface, Power BI empowers users to connect to various data sources, create interactive reports, and share insights effortlessly. Optimising Power BI reports for performance ensures efficient data analysis. What is Power BI, and how does it differ from other data visualisation tools?

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Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. Data Preparation for AI Projects Data preparation is critical in any AI project, laying the foundation for accurate and reliable model outcomes.

Artificial Intelligence 52

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Pickl AI

NOVEMBER 4, 2024

Data Warehousing A data warehouse is a centralised repository that stores large volumes of structured and unstructured data from various sources. It enables reporting and Data Analysis and provides a historical data record that can be used for decision-making.

Data Engineer 52

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DagsHub

APRIL 21, 2024

A traditional machine learning (ML) pipeline is a collection of various stages that include data collection, data preparation, model training and evaluation, hyperparameter tuning (if needed), model deployment and scaling, monitoring, security and compliance, and CI/CD.

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IBM Journey to AI blog

OCTOBER 20, 2023

Major cloud infrastructure providers such as IBM, Amazon AWS, Microsoft Azure and Google Cloud have expanded the market by adding AI platforms to their offerings. Automated development: With AutoAI , beginners can quickly get started and more advanced data scientists can accelerate experimentation in AI development.

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ODSC - Open Data Science

JANUARY 29, 2024

Data Engineering A job role in its own right, this involves managing the modern data stack and structuring data and workflow pipelines — crucial for preparing data for use in training and running AI models. series (Davinci, etc), GPT-4, and GPT-4 Turbo are immensely popular.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

Heartbeat

MAY 29, 2023

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

Machine Learning 78

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Pickl AI

OCTOBER 3, 2024

Data Management Tools These platforms often provide robust data management features that assist in data preparation, cleaning, and augmentation, which are crucial for training effective AI models. Organisations can adjust their usage based on demand without significant infrastructure investments.

Machine Learning 52

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Pickl AI

NOVEMBER 28, 2024

Data Transformation Transforming data prepares it for Machine Learning models. Encoding categorical variables converts non-numeric data into a usable format for ML models, often using techniques like one-hot encoding. Outlier detection identifies extreme values that may skew results and can be removed or adjusted.

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The MLOps Blog

MAY 31, 2023

The objective of an ML Platform is to automate repetitive tasks and streamline the processes starting from data preparation to model deployment and monitoring. There can be multiple sources of data at the same time, which can be available in different forms like image, text, and tabular form. are present in the data.

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The MLOps Blog

OCTOBER 20, 2023

And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis. When data science was sexy , notebooks weren’t a thing yet. Aside neptune.ai

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Pickl AI

NOVEMBER 18, 2024

Key steps involve problem definition, data preparation, and algorithm selection. Data quality significantly impacts model performance. It offers extensive support for Machine Learning, data analysis, and visualisation. Key Takeaways Machine Learning Models are vital for modern technology applications.

Machine Learning 52

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Pickl AI

JUNE 18, 2024

Summary: This blog dives into the most promising Power BI projects, exploring advanced data visualization, AI integration, IoT & blockchain analytics, and emerging technologies. Discover best practices for successful implementation and propel your organization towards data-driven success.

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Pickl AI

DECEMBER 4, 2024

Augmented Analytics Augmented analytics is revolutionising the way businesses analyse data by integrating Artificial Intelligence (AI) and Machine Learning (ML) into analytics processes. Understand data structures and explore data warehousing concepts to efficiently manage and retrieve large datasets.

Data Science 52

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Dataconomy

MARCH 7, 2025

Sales teams can forecast trends, optimize lead scoring, and enhance customer engagement all while reducing manual data analysis. From customer service chatbots to data-driven decision-making , Watson enables businesses to extract insights from large-scale datasets with precision.

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