NYU Center for Data Science

AUGUST 29, 2024

He is partly supported by the Apple Scholars in AI/ML PhD fellowship. This work aims to improve the application of ML in healthcare settings. My goal is to develop methods that can bridge the gap between modern ML and real problems in clinical decision-making.” Standard algorithms aren’t designed for this scenario.

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Towards AI

AUGUST 23, 2024

Simplifying LLM Development: Treat It Like Regular ML Photo by Daniel K Cheung on Unsplash Large Language Models (LLMs) are the latest buzz, often seen as both exciting and intimidating. Like regular ML, LLM hyperparameters (e.g., temperature or model version) should be logged as well.

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Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. Machine Learning In this section, we look beyond ‘standard’ ML practices and explore the 6 ML trends that will set you apart from the pack in 2021.

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The MLOps Blog

MAY 31, 2023

And eCommerce companies have a ton of use cases where ML can help. The problem is, with more ML models and systems in production, you need to set up more infrastructure to reliably manage everything. And because of that, many companies decide to centralize this effort in an internal ML platform. But how to build it?

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ODSC - Open Data Science

OCTOBER 24, 2024

Hypothesis Testing and its Ties to Machine Learning Machine learning can easily become a tool for p-hacking, where we torture the data-finding patterns that are coincidental rather than meaningful. What is the P-Value?

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Ocean Protocol

JANUARY 23, 2024

After a year of hypothesis testing, research sprints and over 20 different data challenges, hackathons, and data science experimentation: the top 10 data challenge participants, ranked by leaderboard points have emerged victorious. Desights is a web3 platform to crowdsource solutions to the toughest AI & ML challenges.

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Pickl AI

NOVEMBER 28, 2024

Introduction Machine Learning ( ML ) is revolutionising industries, from healthcare and finance to retail and manufacturing. As businesses increasingly rely on ML to gain insights and improve decision-making, the demand for skilled professionals surges. This growth signifies Python’s increasing role in ML and related fields.

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Mlearning.ai

MARCH 5, 2023

This can involve calculating summary statistics, such as mean, median, and standard deviation, or conducting hypothesis tests to determine if there are significant differences between groups. Step 3: Data Analysis After visualizing the data, the next step is to analyze the data using numerical methods.

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ODSC - Open Data Science

DECEMBER 7, 2023

ML Pros Deep-Dive into Machine Learning Techniques and MLOps Seth Juarez | Principal Program Manager, AI Platform | Microsoft Learn how new, innovative features in Azure machine learning can help you collaborate and streamline the management of thousands of models across teams. Check out a few of the highlights from each group below.

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AWS Machine Learning Blog

AUGUST 2, 2024

This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Yanyan Zhang is a Senior Generative AI Data Scientist at Amazon Web Services, where she has been working on cutting-edge AI/ML technologies as a Generative AI Specialist, helping customers leverage GenAI to achieve their desired outcomes.

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AWS Machine Learning Blog

JUNE 26, 2024

This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Through thorough research, analysts come up with a hypothesis, test the hypothesis with data, and understand the effect before portfolio managers make decisions on investments as well as mitigate risks associated with their investments.

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Pickl AI

NOVEMBER 4, 2024

Statistics Understand descriptive statistics (mean, median, mode) and inferential statistics (hypothesis testing, confidence intervals). Python’s rich ecosystem offers several libraries, such as Scikit-learn and TensorFlow, which simplify the implementation of ML algorithms.

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DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. Conceptual Soundness of the Model.

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Ocean Protocol

JANUARY 25, 2024

2022 & 2023 data challenges tested different time durations between 7–30 days. It has been determined that initiatives and hypothesis testing that require longer than 20 days will be tagged and executed as something other than a data challenge (data science competition). continue to roll out regularly.

Data Science 52

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Becoming Human

MAY 15, 2023

In Inferential Statistics, you can learn P-Value , T-Value , Hypothesis Testing , and A/B Testing , which will help you to understand your data in the form of mathematics. It provides end-to-end pipeline components for building scalable and reliable ML production systems.

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Mlearning.ai

MAY 1, 2023

It involves hypothesis testing , confidence intervals, and regression analysis. We can use Histograms, Pie Charts, Bar Plots, etc. for the same. Inferential Statistics: It consists of collecting sample data and making conclusions about the data using some experiments.

Data Science 52

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Mlearning.ai

FEBRUARY 11, 2023

example: From above statement, we make a exact opposite, which is smoking does not increase risk of cancer Since it is contrary to null hypothesis, the equations generally have <> (not equal to) , > ,< (A<>B, A<B, A>B) How to conduct Hypothesis testing? Compute the test.

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Dataconomy

AUGUST 22, 2023

Even if your plan on paper is quite simple, creating an algorithm from scratch is complicated and unpredictable, but luckily there are many mathematical theorems you can use for your next ML initiative.

Machine Learning 91

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Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

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Pickl AI

NOVEMBER 5, 2024

AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision. Statistical Knowledge A solid understanding of statistics is fundamental for analysing data distributions and conducting hypothesis testing.

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Pickl AI

SEPTEMBER 23, 2024

Machine Learning Machine Learning (ML) is a crucial component of Data Science. ML models help predict outcomes, automate tasks, and improve decision-making by identifying patterns in large datasets. Hypothesis testing and regression analysis are crucial for making predictions and understanding data relationships.

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Pickl AI

MAY 31, 2023

Accordingly, you need to make sense of the data that you derive from the various sources for which knowledge in probability, hypothesis testing, regression analysis is important. Statistical skills: having a clear idea regarding the procedures of different tasks requires you to have a thorough understanding of statistics.

Data Science 52

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Mlearning.ai

FEBRUARY 12, 2023

We can do hypothesis testing, which seems to resemble classical statistical tests. > B2<-hypothesis(model3, hypothesis = 'Session = 0') > B2 Hypothesis Tests for class b: Hypothesis Estimate Est.Error CI.Lower CI.Upper Evid.Ratio Post.Prob Star 1 (Session) = 0 0.73

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Mlearning.ai

JULY 1, 2023

Introduction Continue reading on MLearning.ai »

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Mlearning.ai

MAY 23, 2023

Let us first understand the meaning of bias and variance in detail: Bias: It is a kind of error in a machine learning model when an ML Algorithm is oversimplified. It is introduced into an ML Model when an ML algorithm is made highly complex. It further performs badly on the test data set. Define bias-variance trade-off?

Data Science 52

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O'Reilly Media

OCTOBER 18, 2022

As for formulas, they have names like standardized mean difference (SMD, Cohen’s d ), the adverse impact ratio (AIR) and four-fifth’s rule threshold, and basic statistical hypothesis testing (e.g., t -, x 2 -, binomial z -, or Fisher’s exact tests).

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ML @ CMU

FEBRUARY 29, 2024

We apply the Bonferroni correction to account for multiple hypothesis testing. Analysis (step 6): We compute the Pearson’s r correlation between the LabintheWild annotations by demographic for the dataset’s original labels and the models’ predictions. Example Annotation.

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Tableau

MARCH 10, 2021

Using AI, ML, and other statistical methods to solve business problems has largely been the domain of data scientists. At Tableau, analysis has always been about letting people ask that next question, explore that next hypothesis, test that next idea.

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Tableau

OCTOBER 14, 2021

Using AI, machine learning (ML), and other statistical methods to solve business problems has largely been the domain of data scientists. While AI, ML, and natural language capabilities can be highly technical, they can also be made approachable. Bring advanced analytics capabilities to more problem-solvers with AI.

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Tableau

OCTOBER 14, 2021

Using AI, machine learning (ML), and other statistical methods to solve business problems has largely been the domain of data scientists. While AI, ML, and natural language capabilities can be highly technical, they can also be made approachable. Bring advanced analytics capabilities to more problem-solvers with AI.

Tableau 95

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Tableau

MARCH 10, 2021

Using AI, ML, and other statistical methods to solve business problems has largely been the domain of data scientists. At Tableau, analysis has always been about letting people ask that next question, explore that next hypothesis, test that next idea.

Tableau 52

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Mlearning.ai

JUNE 6, 2023

They made a hypothesis testing with the Chinchilla model. Using smaller models not only speeds up and reduces the cost of inference, but also makes it simpler for developers and researchers who have limited GPU resources.According to the article by the authors (Jordan et al.,

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