Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves. “Shut up and annotate!”

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IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Supervised machine learning Supervised machine learning is a type of machine learning where the model is trained on a labeled dataset (i.e.,

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Pickl AI

JULY 17, 2023

The ability of unsupervised learning to discover similarities and differences in data makes it ideal for conducting exploratory data analysis. Unsupervised Learning Algorithms Unsupervised Learning Algorithms tend to perform more complex processing tasks in comparison to supervised learning.

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Smart Data Collective

JUNE 4, 2021

it is overwhelming to learn data science concepts and a general-purpose language like python at the same time. Exploratory Data Analysis. Exploratory data analysis is analyzing and understanding data. Machine learning is broadly classified into three types – Supervised.

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Towards AI

JANUARY 10, 2024

Task Orientation How were we doing machine learning almost a year ago? They are called foundation models because, with that wide set of data, you build foundations that need not change every time you adapt it to a specific business use case. And they can handle multiple types of data (images, text, video, and audio).

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Pickl AI

FEBRUARY 22, 2024

The dedicated Statistics module focussing on Exploratory Data Analysis, Probability Theory, and Inferential Statistics. Students learn Maximum Likelihood Estimation, the three M’s of Statistics (Mean, Median, Mode), and critical topics like Central Limit Theorem, Confidence Intervals, Hypothesis Testing, and Linear Regression.

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Pickl AI

FEBRUARY 12, 2024

This theorem is crucial in inferential statistics as it allows us to make inferences about the population parameters based on sample data. Differentiate between supervised and unsupervised learning algorithms. Here is a brief description of the same.

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