Towards AI

JANUARY 30, 2024

The core difference being that vision models focus on modalities of image and video while MultiModal models refer to all data modalities. Source : Image by Author Top N/P Sampling LLMs are next token generation models. Example: LLaVA, LLaMA-Adapter V2, LAVIN Vision Language Models (VLMs) VLMs and LLMs have been used interchangeably.

AI 85

AI AI Natural Language Processing Supervised Learning 85

Mlearning.ai

MARCH 28, 2023

This article will focus on the first part called Source Coding whose main result is that raw data typically has redundancy and can be compressed up to a limit with negligible loss of information. To find the information content of a message we need the probability of observing a message p( x ). This average is called the entropy H.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence ML ML 52

Pickl AI

MARCH 1, 2023

The scope of this article aims to discuss the underlying concept of Hypothesis Testing in statistics, its types and steps, significance level, p-value and common errors in hypothesis testing. Here the focus should be on the random data such that the results are unbiased. It is tested against the evidence inferred from the sample data.

Hypothesis Testing 52

Hypothesis Testing Data Science Business Intelligence Business Intelligence 52

Google Research AI blog

AUGUST 17, 2023

In this post, we focus on the post-training setting: given a pre-trained network, how can we determine which weights should be pruned? Our regression data matrix is ( n x p ), where n is the batch (sub-sample) size and p is the number of weights in the original network. immediately after weight initialization).

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Algorithm Machine Learning Machine Learning 98

Shreyansh Singh

MARCH 26, 2023

They focus on FLOP reduction (which doesn’t always correlate with wall-clock speed) and tend to ignore overheads from memory access (IO).FlashAttention Also, most operations are memory-bound/elementwise operations, e.g. softmax applied on $mathbf{P}$, masking applied to $mathbf{S}$, dropout applied to $mathbf{P}$.

Algorithm 99

Algorithm 99

Mlearning.ai

JANUARY 22, 2024

Applications of Time Series Analysis There are three main application areas in time series analysis: Time series forecasting : The focus is to predict the future values of a time series. We’ll focus on time series forecasting. We will focus on the Moving Average. Here, we will use the p-value. The code is on GitHub.

Python 52

Python Machine Learning Machine Learning ML 52

IBM Data Science in Practice

APRIL 9, 2024

show() import cv2 from towhee.types.image import Image def read_images(img_paths): imgs = [] for p in img_paths: imgs.append(Image(cv2.imread(p), imread(p), 'BGR')) return imgs p_search_img = ( p_search_pre.map('pred', 'pred_images', read_images).output('img', Query an example image ‘test/goldfish/*.JPEG’

Deep Learning 130

Deep Learning Deep Learning Database Data Preparation 130

Dataconomy

OCTOBER 3, 2023

Here’s a sneak peek at what awaits: Pixel p erfection: The event’s spotlight will undoubtedly shine on the Pixel 8 and Pixel 8 Pro, Google’s latest flagship smartphones. While the primary focus is on Pixel devices, rumors swirl about a potential new Chromecast. What to expect from the Google Pixel 8 Event?

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AI AI 103

Data Science Dojo

FEBRUARY 15, 2023

Image Credit: Pinterest – Problem solving tools In last week’s post , DS-Dojo introduced our readers to this blog-series’ three focus areas, namely: 1) software development, 2) project-management, and 3) data science. Digital tech created an abundance of tools, but a simple set can solve everything. Better yet, a riddle.

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K-nearest Neighbors Decision Trees Support Vector Machines Algorithm 195

Mlearning.ai

FEBRUARY 11, 2023

At the moment, we will focus on the user-based algorithm. User-based Collaborative Filtering: This algorithm looks for similar users with the same preferences and recommends items that those similar users have rated highly. User-based Collaborative Filtering Algorithm For an easier explanation, let’s make an example. double denom = 0.0;

Algorithm 52

Algorithm Analytics Analytics ML 52

BAIR

NOVEMBER 14, 2023

We therefore focus on certifiably robust classifiers , which provide a mathematical guarantee that their prediction will remain constant for an $ell_p$-norm ball around an input. This focused setting allows us to introduce feature-convex classifiers, which produce closed-form and deterministic certified radii on the order of milliseconds.

Machine Learning 64

Machine Learning Machine Learning Deep Learning Deep Learning 64

Data Science Dojo

JULY 7, 2023

P ython, for instance, is loved for its simplicity and versatility. The variety of programming languages, including Python, Java, JavaScript, and C++, cater to different project needs. Each has its niche, from web development to systems programming. JavaScript, on the other hand, is the lifeblood of interactive web pages.

Data Science 195

Data Science Data Scientist Decision Trees Python 195

IBM Journey to AI blog

FEBRUARY 8, 2024

In 1997, the Global Reporting Initiative (GRI) was founded with the aim of addressing environmental concerns, though it soon broadened its scope to also focus on social and governance issues. Some strategies focus on excluding industries or organizations that do not meet certain ESG criteria.

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Towards AI

MAY 4, 2023

Output Layer: we will use a layer for the prediction (p) consisting of one neuron. The y output is the ground truth label that will be compared to the MLP output prediction (p) to assess the performance of the model. visualizes the MLP Architecture we will implement. Each training example has a corresponding y output.

Python 81

Python AI AI Artificial Intelligence 81

Kaggle

APRIL 20, 2020

I treat R package recommendation as a binary classification task: a classifier $latex f(u, p)$ takes as input a user $latex u$ and a package $latex p$, and predicts whether the user will install the package or not. In contrast to Model 1 with features derived from metadata, I focus on the user-package rating matrix. instead.

Cross Validation 73

Cross Validation Machine Learning Machine Learning Computer Science 73

Hacker News

JUNE 17, 2023

For example, this will now work: format("{:P}", ptr); P2530 “Hazard pointers for C++26” by Maged M. P2510 “Formatting pointers” by Mark de Wever allows nice formatting of pointer values without incanting reinterpret_cast to an integer type first. Michael, Michael Wong, Paul McKenney, Andrew Hunter, Daisy S.

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Data Science Dojo

FEBRUARY 22, 2023

The platform automatically manages the infrastructure, including server resources, security, and availability, so that you can focus on writing code and delivering value to your customers. With Azure Web Apps, you can host web applications written in a variety of programming languages, such as.NET, Java, PHP, Node.js, and Python.

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Azure Python Machine Learning Machine Learning 370

Towards AI

AUGUST 25, 2023

Russell and P. As a reminder, I highly recommend that you refer to more than one resource (other than documentation) when learning ML, preferably a textbook geared toward your learning level (beginner/intermediate / advanced). In a nutshell, AI Engineering is the application of software engineering best practices to the field of AI.

Machine Learning 96

Machine Learning Machine Learning AI AI 96

ODSC - Open Data Science

OCTOBER 9, 2023

The issue of p-hacking, where data is unfairly manipulated to show statistical importance, is a significant concern. In this rich world of data and experimentation, causal inference stands out as a critical focus for many companies. Causal inference is a core concept that is increasingly becoming a focus in data and experimentation.

Data Science 98

Data Science AI AI Data Scientist 98

Towards AI

AUGUST 16, 2023

When the agent is a computer, the learning process is called machine learning (ML) [6, p. In real-world applications, the focus should be on the data-centric approach. Therefore, I thought it would be helpful to give a complete description of the AI engineering process or AI Process, which is described in most AI/ML textbooks [5][6].

AI 83

AI AI Machine Learning Machine Learning 83

Towards AI

SEPTEMBER 22, 2023

Nucleus sampling or top-p sampling The distribution of token probabilities might be very different, which can bring unexpected results during text generation. Instead of specifying a fixed number of “k” tokens to consider, a probability threshold “p” is used. Generated output: Paris is the city of the future.

Algorithm 57

Algorithm AI AI Machine Learning 57

Towards AI

MAY 15, 2024

It generated the following Manim-based Python script: # Import necessary modules from Manimfrom manim import *class EmbeddingScene(Scene): def construct(self): # Create a matrix representing the embedding matrix embedding_matrix = Matrix([[1, 0.5, 0.3], [0, 0.4, 1]]) embedding_matrix.scale(0.8) Source: Author) What a bummer!

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AI AI Python ML 70

phData

OCTOBER 5, 2023

Over the last month, we’ve been continuing to focus heavily on adding additional support for our Microsoft SQL Server to Snowflake SQL translations. Source: MSSQL SELECT DISTINCT c INTO i FROM p OUTER APPLY OPENJSON(p.PAYLOAD, '$.str') So, what’s new? That’s a great question, and we’re excited to show you. Let’s dive in.

SQL 52

SQL 52

IBM Data Science in Practice

OCTOBER 18, 2023

Smooth Time-Varying Effects: dynamite allow for the estimation of effects that vary over time, using Bayesian P-splines with random walk priors. Define and Estimate Models For this blog, I will focus on the White Blood Cell (WBC) variable to predict sepsis. To use lag variables, click here.

Data Analysis 130

Data Analysis Data Analysis Data Scientist Data Science 130

Data Science Dojo

OCTOBER 31, 2023

In this blog, our focus will be on configuring the gpt-3.5-turbo As a result, the landscape of evaluation practices continues to shift, emphasizing the need for cautious application. In this blog, our focus will be on configuring the gpt-3.5-turbo mkdir -p ‘dataset’ ! mkdir -p ‘dataset’ !

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Mlearning.ai

FEBRUARY 17, 2023

With this template, you’ll be able to focus on the fun part —  experimenting with the OpenAI API and building a unique and powerful AI assistant. Perfect for developers, researchers, or anyone looking to build a ChatGPT app without having to start from scratch. It is a great tool to quickly prototype your idea and improve it as you go.

AI 52

AI AI ML ML 52

Tableau

DECEMBER 23, 2022

link] — Christina P. DataFam Con focuses on using data from geek culture—such as tv series, books, films, and conventions—to practice building visualizations on something that you are passionate about. How did DataFam Con get started? *NEW DATA CHALLENGE* Welcome to #DataFamCon a collab effort hosted by @NicoleKlassen12 and yours truly.

Tableau 52

Tableau Data Visualization 52

Heartbeat

DECEMBER 7, 2023

The researchers start by selecting a set of prompts (P) and a pool of models (M). For each prompt in P and each model in M, a completion is generated. To rank the prompts in P, an offline approach is proposed. The focus is on highlighting the dissimilarity between the responses of the two models.

Deep Learning 52

Deep Learning Deep Learning ML ML 52

Towards AI

MARCH 28, 2023

For example, in English, the sounds /p/ and /b/ are different phonemes because they can change the meaning of a word (e.g., “pat” Computational linguistics and conversational AI are related fields, but they have different focuses and goals. It focuses on the characteristics of individual sounds and how the vocal tract articulates them.

Natural Language Processing 52

Natural Language Processing AI AI Algorithm 52

Towards AI

FEBRUARY 13, 2024

Format for the Persona Pattern: Act as Persona P: Here, you assign the AI a specific role or identity. For example, instead of asking “What’s the weather like?” a more engineered prompt would be “Provide a current weather report for Zurich, including temperature and chance of rain.”

Natural Language Processing 92

Natural Language Processing AI AI Artificial Intelligence 92

Chatbots Life

APRIL 19, 2024

The 2023 Global Trends in AI Report by S&P Global reveals that 69% of respondents pushed at least one AI deployment into production. Their human resources can focus on more strategic endeavors. This, in turn, increases overall productivity and allows staff to focus on higher-value activities. The trends don’t end here.

AI 59

AI AI Artificial Intelligence Artificial Intelligence 59

Towards AI

AUGUST 16, 2023

Therefore, many articles, such as [3] focus on design patterns that can help create more robust and reusable code with fewer bugs. Russell and P. Therefore, the key is to design each component so that most of the work can stay and serve as a foundation for the next stage of development. References [1] E. 15, 2022. [4]

Machine Learning 88

Machine Learning Machine Learning AI AI 88

Towards AI

NOVEMBER 1, 2023

In the second part, we will move our focus to building regression models on how to predict Singapore’s HDB prices. Although the optimum number of lagged variables is three, based on the ARIMA parameter p = 3, we opted to create four lagged variables. For features forecast and trend, we can obtain them directly from our SARIMA model.

AI 98

AI AI Data Science Machine Learning 98

IBM Journey to AI blog

AUGUST 22, 2023

Digital twins and integrated data For the presentation layer, you can leverage various capabilities, such as 3D modeling, augmented reality and various predictive model-based health scores and criticality indices. At IBM, we strongly believe that open technologies are the required foundation of the digital twin.

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AI AI ML ML 80

ODSC - Open Data Science

MAY 1, 2023

Keynotes Raluca Ada Popa, PhD Associate Professor, UC Berkeley | Co-founder and Co-director of UK Berkley RISELab Raluca Ada Popa’s current focus at UC Berkeley is computer security, systems, and applied cryptography. Learn more about them below. Prior to MosaicML, Hagay held AI engineering leadership roles at Meta, AWS, and GE Healthcare.

Data Science 52

Data Science Machine Learning Machine Learning Azure 52

Mlearning.ai

JULY 5, 2023

Let p be the probability of A winning each round, q the probability of B winning each round, W be the event that A wins the game, and pi be the probability that A wins the game when starting with $i. Consider two players A and B participating in a series of bets, transferring money to one another after each bet depending on who wins.

ML 52

ML ML AI AI 52

BAIR

NOVEMBER 14, 2023

We therefore focus on certifiably robust classifiers , which provide a mathematical guarantee that their prediction will remain constant for an $ell_p$-norm ball around an input. This focused setting allows us to introduce feature-convex classifiers, which produce closed-form and deterministic certified radii on the order of milliseconds.

Machine Learning 40

Machine Learning Machine Learning Deep Learning Deep Learning 40