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category mathematics 
Analytics Vidhya
MAY 19, 2023
This field of mathematics helps analyze data and apply the findings to address various data-related issues. There are two broad categories of statistical methods: descriptive and inferential statistics. Statistics involves gathering and organizing raw data into an easily understandable format.
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Hacker News
SEPTEMBER 12, 2023
It has been experimentally confirmed to apply to some categories, but not others, raising questions about when it is applicable and why. I shed some light on these questions by examining the mathematical properties required for the effect and generating mechanisms that can produce them.
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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications
Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization
From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success
Understanding User Needs and Satisfying Them
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know
Hacker News
JULY 23, 2023
Comments (..)
83 Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications
Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization
From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success
Understanding User Needs and Satisfying Them
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know
Data Science Dojo
AUGUST 11, 2023
These models can be used to predict future outcomes or to classify data into different categories. It provides a wide range of mathematical functions and algorithms. Models: Bridging data and predictive insights Models, in the context of data science, are mathematical representations of real-world phenomena.
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Data Science Dojo
MARCH 10, 2024
Some common uses in this category include code generation and quality control. Anthropic’s AI chatbot outperformed its competitors in undergraduate-level knowledge, graduate-level reasoning, and basic mathematics. It is also useful for sales-related functions like product recommendations, forecasting, and targeted marketing.
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Chatbots Life
APRIL 16, 2024
Generative models focus on capturing the underlying patterns of data to generate new examples that resemble the original dataset, while discriminative models concentrate on classifying or discriminating between different categories based on input features. Can you provide examples of generative models?
Pickl AI
APRIL 11, 2023
The broader classification of variables falls under the following categories: Qualitative variable -It includes the data that doesn’t hold a quantifiable or numerical value. Nominal and ordinal variables are sub-categories of qualitative variables. It can be further subdivided into nominal and ordinal variables.
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DataRobot
AUGUST 25, 2021
In a recent blog, we talked about how, at DataRobot , we organize trust in an AI system into three main categories: trust in the performance in your AI/machine learning model , trust in the operations of your AI system, and trust in the ethics of your modelling workflow, both to design the AI system and to integrate it with your business process.
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Hacker News
JANUARY 31, 2024
Above: Many small business figured out the hard way why coupon sites generate worse users Incentive programs often don’t perform The people you attract with referral programs, free trials, coupons, and gamification — folks who are “incentivized” as a broad umbrella category — are usually MUCH WORSE than organic ones.
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Dataconomy
AUGUST 28, 2023
There are mathematical theorems that support the working principle of all automation systems that make up a large part of our daily lives. Think of kernels as mathematical functions that take in data points and output their relationships in a higher-dimensional space.
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Towards AI
FEBRUARY 13, 2024
Artists can also decide what content categories their voice can be used for. FunSearch: Making new discoveries in mathematical sciences using LLMs FunSearch is a method to search for new mathematics and computer science solutions. This article shared the practices and techniques for improving data quality.
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Becoming Human
AUGUST 15, 2023
Instead, it is a fundamental tool for classification tasks, helping us predict whether something belongs to one of two categories, like yes/no, true/false, or spam/not spam. It may sound complex, but it’s just a mathematical function that squashes any input to a value between 0 and 1. What is Logistic Regression? Sigmoid Function.
Pickl AI
NOVEMBER 2, 2023
Statistics and Mathematics Data Science heavily relies on statistical analysis. Expertise in mathematics and statistical fields is essential for deciding algorithms, drawing conclusions, and making predictions. Cheat sheets in this category offer guidance on cleaning, feature engineering, and scaling data.
Mlearning.ai
MAY 12, 2023
SVM Mathematical Intuition. The best-Fit line separating the categories In Support Vector Classifier (SVC) , also we try to find the best-fit line but along with that we also try to calculate two marginal planes(P1 and P2). I will cover only the first 5 subtopics in this article and will cover the rest in my next upcoming article.
IBM Journey to AI blog
MAY 1, 2023
Continued advancement in AI development has resulted today in a definition of AI which has several categories and characteristics. The four categories of predictive modelling, robotics, speech and image recognition are collectively known as algorithm-based AI or Discriminative AI. It has taken the world by storm.
Mlearning.ai
MAY 22, 2023
Today we will continue discussing SVMs and will try to understand the mathematics behind SVMs, cost function, Support Vector Regressor (SVR), and Support Vector Kernels. Source: Alteryx SVM Mathematical Intuition In the image below, we have a best-fit line or a plane separating positive and negative lines.
ODSC - Open Data Science
NOVEMBER 16, 2023
Study Hopes to Unlock the Potential of LLMs in Mathematical Problem-Solving A study hopes to show how LLMs can overcome mathematical hurdles and significantly improve their arithmetic problem-solving capabilities. Dan will address the four categories of catastrophic AI risks: malicious use, AI race, organizational risks, and rogue AIs.
Smart Data Collective
JUNE 4, 2021
Data science needs knowledge from a variety of fields including statistics, mathematics, programming, and transforming data. Mathematics, statistics, and programming are pillars of data science. Mathematics. The following branches of mathematics are important for data science. Where to start? Linear Algebra.
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Towards AI
FEBRUARY 20, 2024
While the first mathematical model of a neural network was published way back in 1943, modern AI research really kicked off in the 1950s. Artificial Intelligence” is a term situated in the same category of other terms such as “strategy,” “consciousness,” “value” and “morality,” a group conveniently labeled “suitcase words” by Marvin Minsky.
Smart Data Collective
NOVEMBER 19, 2020
Nominal categories are specific, independent groups. Ratios are data categories which contain no zero. Here take a look at the most common data visualizations techniques, depending on the categories of variables. In the diagram, categories are shown in descending order of the frequency, wherein the frequency represents no.
DataRobot
OCTOBER 26, 2021
DataRobot organizes the concept of trust in an AI system into three main categories: performance, operations, and ethics. Within these categories are thirteen dimensions of trust that, when seen holistically, constitute a system that can earn your trust. Dimensions of trust.
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PyImageSearch
FEBRUARY 6, 2023
The Vegetable Image Dataset comprises 15 vegetable images, with 224×224 color images of 21,000 different vegetables from 15 categories and 1400 images per category. Figure 2 shows 9 of the 15 vegetable image categories from the dataset. Figure 2: Analyzing a few categories from the vegetable image classification dataset.
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Mlearning.ai
JULY 23, 2023
Text Classification : Categorizing text into predefined categories based on its content. This is a process where we assign predefined categories, or labels, to text based on its content. In the training phase, a machine learning algorithm is fed a large amount of labeled data — text documents already assigned to specific categories.
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PyImageSearch
JANUARY 9, 2023
Next, in the third part, we will understand the concept and mathematical formulation of triplet loss and write our own loss function in Keras and TensorFlow. Mathematically, we want to learn the parameters such that the distance between the features and , that is, approximates the similarity between the inputs and. where is a margin.
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Pickl AI
MARCH 15, 2024
product categories), and adding context to visualizations. Numerical Values Analyze sales figures, calculate averages, and perform mathematical operations. Product Filter: Add a product filter to enable users to focus on specific products or product categories. Ensure consistent formatting (e.g., year-over-year sales).
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Smart Data Collective
MAY 29, 2023
Three Different Analysts Data analysis as a whole is a very broad concept which can and should be broken down into three separate, more specific categories : Data Scientist, Data Engineer, and Data Analyst. Here are the differences, generally speaking. Data Scientist These employees are programmers and analysts combined.
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Pickl AI
OCTOBER 12, 2023
NumPy furnishes a wide spectrum of data types that can be classified into the following primary categories: Integer Data Types: Integers, being whole numbers devoid of decimal fractions, are encompassed by NumPy’s repertoire of data types. What are the Different Data Types in NumPy?
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AWS Machine Learning Blog
MARCH 4, 2024
Source: [link] Specifically, Opus outperforms its peers on most of the common evaluation benchmarks for AI systems, including undergraduate level expert knowledge (MMLU), graduate level expert reasoning (GPQA), basic mathematics (GSM8K), and more.
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Dataconomy
AUGUST 16, 2023
These models can predict future events, classify data into categories, or uncover relationships between variables, enabling better decision-making. Suppose you have a bachelor’s degree in a related field, such as computer science, mathematics, or statistics. As we ponder “What does a data scientist do?
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AWS Machine Learning Blog
OCTOBER 18, 2023
It is already trained on tens of millions of images across many categories. Instead of thousands of images, you can upload a small set of training images (typically a few hundred images or less per category) that are specific to your use case. Matthew has a Mathematics PhD and enjoys rock climbing and music in his free time.
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Smart Data Collective
JUNE 5, 2021
It’s based on a series of mathematical equations that can be fairly complex to comprehend, but fortunately the process is easy to understand in essence. Although the very mention of mathematics and equations may seem daunting, LSI is actually a concept that anybody who has entered a query into Google will be familiar with to some extent.
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Hacker News
MARCH 11, 2024
The immediate problem “is” that it’s Too Easy By Default to write security and safety vulnerabilities in C++ that would have been caught by stricter enforcement of known rules for type, bounds, initialization, and lifetime language safety In C++, we need to start with improving these four categories. issues with C++.
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Pickl AI
AUGUST 29, 2023
It mainly involves creating representations or models for capturing underlying patterns, structures and associations in data, mathematically. Model Building: You further need to apply your chosen technique for building the mathematical model representing the relationship between the variables.
Snorkel AI
AUGUST 16, 2023
The vast majority of AI systems fall under the category of discriminative AI. These systems predict numeric or categorical values about particular subjects based on their mathematical understanding of the feature space. The main, top-of-mind dangers of genAI fall into three categories: Intellectual property violation.
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Snorkel AI
AUGUST 16, 2023
The vast majority of AI systems fall under the category of discriminative AI. These systems predict numeric or categorical values about particular subjects based on their mathematical understanding of the feature space. The main, top-of-mind dangers of genAI fall into three categories: Intellectual property violation.
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Pickl AI
JULY 25, 2023
Additionally, these roles may overlap in some cases, and individuals with these job titles might possess skills from multiple categories. Data Focus Structured, Semi- structured, and unstructured data Structured and unstructured data from various sources (e.g., Data Engineer v/s Data Scientist: Which is Better?
Mlearning.ai
MARCH 6, 2023
Conditional GANs (CGANs): These are GANs that take in additional information, such as labels or class information, to generate samples that belong to a specific class or category. GANs are constructed as a minimax game in which the Discriminator seeks to minimize its reward V(D, G).
ODSC - Open Data Science
MARCH 8, 2024
This means that, for example, the embeddings representing two words or concepts that are semantically similar, will be mathematically close within the multi-dimensional space. It can perform various image classification tasks by simply providing the names of the visual categories in natural language, without any fine-tuning or labeled data.
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ODSC - Open Data Science
OCTOBER 31, 2023
Note: My orange line is a metaphorical one; it’s not mathematically correct, but hopefully you get my point. We’re seeing a number of generative AI fall into this category. As data becomes more complex, it becomes harder to query. This is further amplified when scaled (the size of the dataset, and the number of predictions being made).
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Dataconomy
MARCH 24, 2023
A degree in computer science, mathematics, statistics, or a related field is often preferred. Educational background Degrees: Many BI professionals have degrees in computer science, information systems, mathematics, or statistics. They may also be involved in thought leadership and business development. According to the U.S.
Dataconomy
MARCH 24, 2023
A degree in computer science, mathematics, statistics, or a related field is often preferred. Educational background Degrees: Many BI professionals have degrees in computer science, information systems, mathematics, or statistics. They may also be involved in thought leadership and business development. According to the U.S.
Dataconomy
APRIL 18, 2023
Machine learning techniques can be broadly classified into three categories: supervised learning, unsupervised learning, and reinforcement learning. AI algorithms can be classified into two broad categories: symbolic or rule-based algorithms and numerical or statistical algorithms.
Hacker News
DECEMBER 4, 2023
We will make a fundamental category error. And when we do that, we are making a category error. Both language and the laws make this an easy category error to make. Corporations like that we make this category error—see, I just made it myself—because they profit when we think of them as friends.
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Pickl AI
SEPTEMBER 12, 2023
Interdisciplinary Nature Data Science combines elements of computer science, statistics, mathematics, and domain-specific knowledge. Prerequisites Check if the course has any specific prerequisites, such as prior knowledge of programming, mathematics, or statistics. Choose one that aligns with your availability and commitments.
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