Mlearning.ai

JANUARY 26, 2023

Which commercial Data Cube (covering the whole of EU / whole of world / majority of global EO data) services currently exists and what is the best way to use them for projects? One way to make EO and environmental data more usable is to organize them through Cloud data services as Data Cubes.

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AWS Database Clean Data Data Science 98

DrivenData Labs

MARCH 30, 2023

Privacy-enhancing technologies (PETs) have the potential to unlock more trustworthy innovation in data analysis and machine learning. Federated learning is one such technology that enables organizations to analyze sensitive data while providing improved privacy protections. That’s why the U.S. The goal of the U.S.-U.K. This post introduces the U.S.

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Mlearning.ai

JULY 24, 2023

One clever way to improve predictions is by combining multiple decision trees, aggregating their outputs, and predicting the final outcome based on the average (for regression) or majority voting (for classification). Decision trees are commonly used in classification and regression tasks and can efficiently handle large datasets.

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Mlearning.ai

FEBRUARY 28, 2023

You can find the project codes below: GitHub - joshuavaple/yelp-review: refactored codes for YELP review regression 2. Writing More Production-Ready Data Science Project (Part 2): Creating a Web App with Streamlit and Deploying to Google Cloud Run with Docker Photo by Venti Views on Unsplash 1. file inside streamlit folder. works, app.py

Data Science 52

Data Science Python ML ML 52

Victor Zhou

APRIL 10, 2019

I wrote an entire blog post about one way to do this using a metric called Gini Impurity. ← If you didn’t, here’s a very short TL;DR: We can use Gini Impurity to calculate a value called Gini Gain for any split. In my opinion, most Machine Learning tutorials aren’t beginner-friendly enough. Let’s dive in. Let’s dive in. Blue, right?

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Mlearning.ai

FEBRUARY 6, 2023

A Sagemaker processing job is one of the easiest ways since it focuses on abstracting away the infrastructure needed. values text2 = df["text2"].values values # Create the trainer for inference. We’ll be using Amazon Sagemaker, a fully managed machine learning service. More on this is discussed later.

AWS 52

AWS ML ML Python 52

Pickl AI

JANUARY 12, 2023

After the completion of the course, they can perform data analysis and build products using R. In the competitive times like today, working professionals should always look for upskilling themselves. However, career expansion becomes challenging. After working for certain years, the professional journey becomes stagnant.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Tableau

JANUARY 27, 2021

January 27, 2021 - 4:36pm. It’s been amazing to see the way this community came together this past year to help each other and use data to understand everything going on around us. We believe customers all over the world are broadly deploying Tableau because it provides incredible value and drives real business outcomes.

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Tableau

JANUARY 27, 2021

January 27, 2021 - 4:36pm. It’s been amazing to see the way this community came together this past year to help each other and use data to understand everything going on around us. We believe customers all over the world are broadly deploying Tableau because it provides incredible value and drives real business outcomes.

Tableau 52

Tableau Business Intelligence Business Intelligence Analytics 52

Heartbeat

AUGUST 16, 2023

As a DIY hacker, I try to find out unique ways to collect data. Introduction With the increase in visual data, it can be hard to sort and classify videos, making it difficult for Search Engine Optimization (SEO) algorithms to sort out the video data. So for this project, I found a quick hack. Go to [link] and log in.

Python 52

Python Deep Learning Deep Learning ML 52

O'Reilly Media

SEPTEMBER 15, 2021

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. The results gave us insight into what our subscribers are paid, where they’re located, what industries they work for, what their concerns are, and what sorts of career development opportunities they’re pursuing. Executive Summary.

AI 145

AI AI Azure AWS 145

Mlearning.ai

FEBRUARY 17, 2023

For this tutorial, we’re going to create 3 prompt templates each one has its way of how we want the AI to behave (AI assistant, English to other languages, and image generator). 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. and OpenAI.

AI 52

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PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al. Object detection is no different.

Deep Learning 120

Deep Learning Deep Learning Algorithm Support Vector Machines 120

Dataconomy

MAY 8, 2023

The constantly rising number of AI drawing generators is making it hard to find which one best fits your needs. According to reports , a lucrative decade for the artificial intelligence (AI) industry is on the way, and AI drawing generators from texts is one of the starters of the trend.

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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. Labeled data might be also like uranium.

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PyImageSearch

NOVEMBER 6, 2023

Throughout our journey, we’ve traversed the landscapes of various autoencoder architectures, each with its unique strengths and applications. In this concluding tutorial, we’ll delve deep into the captivating world of image segmentation, harnessing the power of the U-Net architecture. Looking for the source code to this post?

Deep Learning 67

Deep Learning Deep Learning Python Data Preparation 67

BAIR

OCTOBER 16, 2023

What if we performed RL in a comparative way? Large Language Models (LLMs) have powered increasingly capable virtual assistants, such as GPT-4 , Claude-2 , Bard and Bing Chat. Figure 1: This diagram illustrates the difference between reinforcement learning from absolute feedback and relative feedback.

Algorithm 90

Algorithm 90

Victor Zhou

APRIL 25, 2019

2022 Update : thank you all for tremendous support this guide has received! I’ve modernized some of the code and content in this post. Happy developing ? came out in 2015, it inspired a new.io game genre that has since exploded in popularity. I experienced the rise of.io games firsthand: I’ve built and sold 2.io io games in the past 3 years.

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phData

FEBRUARY 29, 2024

These strategies will range from ways to reduce the size of your data, to your query structure. In each section, you will find examples that demonstrate how to implement each strategy and drive the desired outcome. database permissions, ETL capability, processing, etc.), it has to be done using custom SQL in Tableau?

Tableau 52

Tableau SQL Database ETL 52

AWS Machine Learning Blog

NOVEMBER 22, 2023

Use the “Generative AI” tag as you are browsing the session catalog to find them. Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. And although generative AI has appeared in previous events, this year we’re taking it to the next level.

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AWS ML ML AI 112

AWS Machine Learning Blog

JANUARY 12, 2024

Enterprises have access to massive amounts of data, much of which is difficult to discover because the data is unstructured. Conventional approaches to analyzing unstructured data use keyword or synonym matching. They don’t capture the full context of a document, making them less effective in dealing with unstructured data.

Natural Language Processing 114

Natural Language Processing AWS Data Science Database 114

PyImageSearch

JANUARY 23, 2023

Table of Contents Scaling Kaggle Competitions Using XGBoost: Part 4 What Is XGBoost? Our Dummy Dataset Breaking Down the Math Configuring Your Development Environment Having Problems Configuring Your Development Environment? If you have stuck with us through the entire journey till now (Great work!), Looking for the source code to this post?

Deep Learning 107

Deep Learning Deep Learning Algorithm Decision Trees 107

BAIR

OCTOBER 16, 2023

What if we performed RL in a comparative way? Large Language Models (LLMs) have powered increasingly capable virtual assistants, such as GPT-4 , Claude-2 , Bard and Bing Chat. Figure 1: This diagram illustrates the difference between reinforcement learning from absolute feedback and relative feedback.

Algorithm 40

Algorithm 40

Hacker News

JUNE 28, 2023

We’ve worked very hard to make its design as clean and coherent as possible—and to make it a timeless way to elegantly represent computation and everything that can be described through it. Because with the advent of LLMs our language has become a unique bridge between humans, AIs and computation.

Machine Learning 182

Machine Learning Machine Learning AI AI 182

PyImageSearch

NOVEMBER 20, 2023

The previous one was all about introducing Causality in the briefest way possible. You can find it right here. Tools and Methodologies for Studying Causal Effects Welcome back to Part 3 of the 5-part series on Causality in Machine Learning. Picking up where we left off, let us revise what we learned in Part 1. What do I mean by that?

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Deep Learning Deep Learning Machine Learning Machine Learning 67

PyImageSearch

JANUARY 8, 2024

Home Table of Contents Adversarial Learning with Keras and TensorFlow (Part 1): Overview of Adversarial Learning Configuring Your Development Environment Need Help Configuring Your Development Environment? We will understand the dataset and the data pipeline for our application and discuss the salient features of the NSL framework in detail.

Deep Learning 64

Deep Learning Deep Learning Data Pipeline Computer Science 64

AssemblyAI

NOVEMBER 21, 2022

Finding efficient and fast matrix multiplication algorithms is therefore paramount given that they will supercharge every neural network, potentially allowing us to run models prohibited by our current hardware limitations. The method employs AlphaTensor , an AI-based system that operates on Deep Reinforcement Learning.

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The MLOps Blog

JANUARY 19, 2024

We’ll look at ways to reduce a model’s memory footprint, speed up training, and best practices for monitoring. Imagine you’re facing the following challenge: you want to develop a Large Language Model (LLM) that can proficiently respond to inquiries in Portuguese. You have a valuable dataset and can choose from various base models.

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Natural Language Processing ML ML Machine Learning 52

The MLOps Blog

MAY 10, 2023

When working on real-world machine learning (ML) use cases, finding the best algorithm/model is not the end of your responsibilities. Saving and storing your model the right way takes care of this. It is crucial to save, store, and package these models for their future use and deployment to production. into a single deployable package.

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Python ML ML Database 105

PyImageSearch

JUNE 19, 2023

Each service uses unique techniques and algorithms to analyze user data and provide recommendations that keep us returning for more. This is done by finding the item, denoted as , with the highest utility score when measured against the user. Figure 1: Distribution of applications of recommendation systems (source: Ko et al.,

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K-nearest Neighbors Clustering Algorithm Deep Learning 56

PyImageSearch

JANUARY 22, 2024

The underlying model, often a neural network, is trained to predict a way to slightly denoise the image in each step. Home Table of Contents Getting Started with Diffusers for Text-to-Image Introduction A Brief Primer on Diffusion Configuring Your Development Environment Need Help Configuring Your Development Environment?

Deep Learning 64

Deep Learning Deep Learning Algorithm Artificial Intelligence 64

Pickl AI

JULY 12, 2023

The aggregation includes functions like average, summation, accounting and finding the maximum or minimum values. We are living in a world where data drives decisions. Also, it is making transformative changes across the business nations. Data manipulation in Data Science is the fundamental process in data analysis.

Data Analysis 52

Data Analysis Data Analysis Database Clean Data 52

PyImageSearch

SEPTEMBER 18, 2023

In the previous tutorial , we discussed the former in detail to understand how SAM can be prompted in different ways to segment specific regions in any image in real-time. Looking for the source code to this post? zero-shot image classification, text-to-image retrieval, and image similarity).

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Hacker News

FEBRUARY 3, 2023

This is part 1 in a 3-part series about the Second Law: 1. Computational Foundations for the Second Law of Thermodynamics 2. A 50-Year Quest: My Personal Journey with the Second Law of Thermodynamics 3. How Did We Get Here? The Tangled History of the Second Law of Thermodynamics The Mystery of the Second Law Entropy increases.

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PyImageSearch

DECEMBER 26, 2022

The best way to tune the knobs is to use the gradient of the objective function with respect to all the individual knobs as a signal. This tutorial will apply the concepts and work our way into understanding an automatic differentiation Python package from scratch. Having Problems Configuring Your Development Environment?

Deep Learning 52

Deep Learning Deep Learning Python Artificial Intelligence 52

PyImageSearch

SEPTEMBER 25, 2023

YouTube is the world’s largest platform to create, consume, and share video content. Their recommendations ( Figure 1 ) help billions of users discover personalized content from an ever-growing corpus of videos. Figure 1: YouTube video recommendations on mobile app (source: Covington et al., RecSys’16 ).

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Deep Learning Deep Learning Algorithm Machine Learning 120

Flipboard

NOVEMBER 27, 2023

A Brief Introduction to Do-Calculus Welcome back to Part 4 of the series on Causality in Machine Learning. In simple words, this means to identify the effect or effects for a particular cause from data that is continuous rather than having discrete values. Well, that’s a mouthful. What do we mean by that?

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Deep Learning Deep Learning Machine Learning Machine Learning 76