Smart Data Collective

NOVEMBER 18, 2020

You should learn what a big data career looks like , which involves knowing the differences between different data processes. This new approach has proven to be much more effective, so it is a skill set that people must master to become data scientists. Where to Use Data Science? Where to Use Data Mining?

Data Mining 143

Data Mining Data Mining Data Mining Data Science 143

Pickl AI

MAY 31, 2023

Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science. Why learn Python for Data Science? Being one of the most demanding programming languages today, you need to learn Python for Data Science. The ease of learning enables you to begin programming with Python as the most ideal tool.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

PyImageSearch

APRIL 24, 2023

This tutorial is primarily for developers who want to accelerate their deep learning models with PyTorch 2.0. In this series, you will learn about Accelerating Deep Learning Models with PyTorch 2.0. This lesson is the 2nd of a 2-part series on Accelerating Deep Learning Models with PyTorch 2.0 : What’s New in PyTorch 2.0?

Deep Learning 103

Deep Learning Deep Learning Python Computer Science 103

Kaggle

SEPTEMBER 9, 2020

Introduction I participated in machine learning (ML) competitions at Kaggle and other platforms to build machine learning muscles. I loved new learnings but ignored the value that old ML pipelines could bring. Feel free to check it out. Here at Kaggle we’re excited to showcase the work of our Grandmasters.

Machine Learning 82

Machine Learning Machine Learning Deep Learning Deep Learning 82

Alation

FEBRUARY 2, 2023

They are knowledgeable about the different tools and technologies used in the industry, such as programming languages, data processing frameworks, machine learning libraries, databases, and analytics platforms for call history. Data product managers are in high demand these days. So what sets data product managers apart from the pack?

Analytics 52

Analytics Analytics Machine Learning Machine Learning 52

Heartbeat

DECEMBER 22, 2023

Want to learn how to build modern software with LLMs using the newest tools and techniques in the field? Want to learn how to build modern software with LLMs using the newest tools and techniques in the field? Check out this free LLMOps course from industry expert Elvis Saravia of DAIR.AI! " ) tools = [search_tool] ?

Data Science 52

Data Science Data Scientist Deep Learning Deep Learning 52

PyImageSearch

NOVEMBER 20, 2023

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. The previous one was all about introducing Causality in the briefest way possible. You can find it right here.

Deep Learning 67

Deep Learning Deep Learning Machine Learning Machine Learning 67

PyImageSearch

OCTOBER 2, 2023

Jump Right To The Downloads Section A Deep Dive into Variational Autoencoder with PyTorch Introduction Deep learning has achieved remarkable success in supervised tasks, especially in image recognition. In our previous tutorial on autoencoders , we learned that they are not inherently generative. Let’s get started!

Deep Learning 120

Deep Learning Deep Learning Clustering Computer Science 120

PyImageSearch

FEBRUARY 27, 2023

Table of Contents Learning JAX in 2023: Part 2 — JAX’s Power Tools grad , jit , vmap , and pmap ?? Summary Citation Information Learning JAX in 2023: Part 2 — JAX’s Power Tools grad , jit , vmap , and pmap In this tutorial, you will learn the power tools of JAX, grad , jit , vmap , and pmap.

Machine Learning 107

Machine Learning Machine Learning Deep Learning Deep Learning 107

PyImageSearch

OCTOBER 23, 2023

Learning on your employer’s administratively locked system? We’ll explore tasks ranging from reconstructing the validation set to sampling from the standard normal distribution, probing the first 50 latent dimensions, and even enhancing visual attributes through the magic of latent space arithmetic. Let’s dive in!

Deep Learning 67

Deep Learning Deep Learning Computer Science Computer Science 67

PyImageSearch

NOVEMBER 6, 2023

In this concluding tutorial, we’ll delve deep into the captivating world of image segmentation, harnessing the power of the U-Net architecture. You’ll also appreciate the pivotal role of image segmentation in various applications, from medical imaging to autonomous driving, and how U-Net stands out as a beacon in this domain.

Deep Learning 67

Deep Learning Deep Learning Python Data Preparation 67

PyImageSearch

JUNE 19, 2023

We will start by learning the basics of these systems and then delve into some of the most popular ones in detail. machine learning, statistics, probability, and algebra) are used to achieve this. machine learning, statistics, probability, and algebra) are employed to recommend our popular daily applications.

K-nearest Neighbors 56

K-nearest Neighbors Clustering Algorithm Deep Learning 56

Heartbeat

OCTOBER 26, 2023

Try this free LLMOps course from industry-expert Elvis Saravia of DAIR.AI! ?️ Imagine harnessing the power of multiple state-of-the-art language models through one unified interface. Imagine harnessing the power of multiple state-of-the-art language models through one unified interface. The beauty of LangChain is its inherent adaptability.

Machine Learning 52

Machine Learning Machine Learning Computer Science Computer Science 52

Mlearning.ai

AUGUST 11, 2023

I learned it all the hard way, so that you don’t have to. Recently, I curated a long list of list of prompts  — feel free to check them for inspiration. I hope they will be useful for you on your journey to becoming a master prompt engineer. Prompt Design Masterclass: The Art of the Prompt. Prompts, prompts, prompts.

Database 98

Database AI AI ML 98

PyImageSearch

JANUARY 23, 2023

The reasoning behind that is simple; whatever we have learned till now, be it adaptive boosting, decision trees, or gradient boosting, have very distinct statistical foundations which require you to get your hands dirty with the math behind them. In this tutorial, you will learn the magic behind the critically acclaimed algorithm: XGBoost.

Deep Learning 107

Deep Learning Deep Learning Algorithm Decision Trees 107

AWS Machine Learning Blog

NOVEMBER 15, 2023

Diving deeper into Llama 2’s architecture, Meta reveals that the model’s fine-tuning melds supervised fine-tuning (SFT) with reinforcement learning aided by human feedback (RLHF). To learn more about how IAM works with SageMaker, refer to Identity and Access Management for Amazon SageMaker.

AWS 97

AWS Artificial Intelligence Artificial Intelligence AI 97

Flipboard

APRIL 17, 2023

Home Table of Contents Learning JAX in 2023: Part 3 — A Step-by-Step Guide to Training Your First Machine Learning Model with JAX Configuring Your Development Environment Having Problems Configuring Your Development Environment? ? Looking for the source code to this post? Looking for the source code to this post?

Machine Learning 107

Machine Learning Machine Learning Deep Learning Deep Learning 107

The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Nice to have you here, Miki.

ML 52

ML ML Data Scientist Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 14, 2023

Please read this post to learn how to implement the RAG approach with Amazon Kendra. Unstructured data accounts for 80% of all the data found within organizations, consisting of repositories of manuals, PDFs, FAQs, emails, and other documents that grows daily.

AWS 101

AWS AI AI Data Silos 101

Hacker News

FEBRUARY 2, 2023

There were several shelves of physics books at the local bookstore. But what I coveted most was the largest physics book collection there: a series of five plushly illustrated college textbooks. But what I coveted most was the largest physics book collection there: a series of five plushly illustrated college textbooks.

Machine Learning 159

Machine Learning Machine Learning Algorithm Analytics 159

PyImageSearch

JULY 17, 2023

It keeps our datasets safe, available, and hassle-free. It’s free, easy to create, and won’t demand your firstborn in return. We will then explore different testing situations (e.g., visualizing the latent space, uniform sampling of data points from this latent space, and recreating images using these sampled points).

Deep Learning 98

Deep Learning Deep Learning Python Machine Learning 98

PyImageSearch

DECEMBER 19, 2022

This is the 2nd lesson in our 4-part series on OAK-101 : Introduction to OpenCV AI Kit (OAK) OAK-D: Understanding and Running Neural Network Inference with DepthAI API (today’s tutorial) OAK 101: Part 3 OAK 101: Part 4 To learn how DepthAI API works and run neural network inference on OAK-D, just keep reading.

Deep Learning 52

Deep Learning Deep Learning Python AI 52

PyImageSearch

DECEMBER 12, 2022

Setting Up the Prerequisites Building the Model Assessing the Model Summary Citation Information Scaling Kaggle Competitions Using XGBoost: Part 2 In our previous tutorial , we went through the basic foundation behind XGBoost and learned how easy it was to incorporate a basic XGBoost model into our project. Table 1: The Dataset.

Decision Trees 52

Decision Trees Deep Learning Deep Learning Exploratory Data Analysis 52

PyImageSearch

SEPTEMBER 11, 2023

Furthermore, you will learn how SAM can be used for making segmentation predictions in real-time and how you can integrate it with your own computer vision projects. To learn how to use SAM in your own projects, just keep reading. Looking for the source code to this post?

AI 117

AI AI Deep Learning Deep Learning 117

Heartbeat

NOVEMBER 9, 2023

Want to learn how to build modern software with LLMs using the newest tools and techniques in the field? Check out this free LLMOps course from industry expert Elvis Saravia of DAIR.AI. Enter the world of Document Chains in LangChain, a revolutionary approach that promises to redefine how we interact with expansive textual data.

Deep Learning 52

Deep Learning Deep Learning Data Scientist ML 52

PyImageSearch

MAY 15, 2023

This lesson is the 2nd in our 3-part series on OAK 102 : Training the YOLOv8 Object Detector for OAK-D Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time (today’s tutorial) OAK 102 (lesson 3) To learn how to run a hand gesture recognition application on OAK-D, just keep reading. Looking for the source code to this post?

Deep Learning 102

Deep Learning Deep Learning Python Algorithm 102

Mlearning.ai

SEPTEMBER 6, 2023

Now, where’s the spellbook — where can I learn it? I’ve ventured there to identify the best free prompt engineering resources, from beginner incantations to advanced conjuring for text, code and AI artistry. There’s no shortage of paid courses, degrees, tutorials, — even complete university programs. But fear not! Let’s dive in! ?✨

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

ML Review

MAY 3, 2018

In our previous work , we briefly attempted to outline Computer Vision’s claim on intelligence; building systems that can learn, infer and reason about the world from visual data alone. An experience that weighs learning heavily. Thanks for reading!

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Machine Learning 52