Best Vuejs Podcasts (2024)

1
Vue.js: The Progressive JavaScript Framework for Modern Web Applications 6:59

2h ago6:59

6:59

Vue.js is an open-source JavaScript framework used for building user interfaces and single-page applications. Created by Evan You in 2014, Vue.js has quickly gained popularity among developers for its simplicity, flexibility, and powerful features. It is designed to be incrementally adoptable, meaning that it can be used for everything from enhanci…

1
Ruby: A Dynamic, Elegant Programming Language for Web Development and Beyond 3:44

2h ago3:44

3:44

Ruby is a dynamic, open-source programming language known for its simplicity, elegance, and productivity. Created by Yukihiro "Matz" Matsumoto in the mid-1990s, Ruby was designed with the principle of making programming both enjoyable and efficient. The language’s intuitive syntax and flexibility make it a favorite among developers, especially for …

1
TypeScript and Content Creation (with Matt Pocock) 57:17

2h ago57:17

57:17

This episode of DejaVue includes not only knowledge but also a certain degree of magic, as Alex and Michael meet up with the one and only TypeScript Wizard Matt Pocock. Together, they talk about how he became a full-time educator and what the pros and cons are, then of course discussing everything around TypeScript - from Types vs. Interfaces, any …

1
ReactJS: A Powerful Library for Building Dynamic User Interfaces 5:09

2h ago5:09

5:09

ReactJS is a popular open-source JavaScript library used for building user interfaces, particularly single-page applications where a seamless user experience is key. Developed and maintained by Facebook, ReactJS has become a cornerstone of modern web development, enabling developers to create complex, interactive, and high-performance user interfac…

1
Apache Spark: The Unified Analytics Engine for Big Data Processing 29:04

1h ago29:04

29:04

Apache Spark is an open-source, distributed computing system designed for fast and flexible large-scale data processing. Originally developed at UC Berkeley’s AMPLab, Spark has become one of the most popular big data frameworks, known for its ability to process vast amounts of data quickly and efficiently. Spark provides a unified analytics engine …

1
Clojure: A Dynamic, Functional Programming Language for the JVM 3:43

1h ago3:43

3:43

Clojure is a modern, dynamic, and functional programming language that runs on the Java Virtual Machine (JVM). Created by Rich Hickey in 2007, Clojure is designed to be simple, expressive, and highly efficient for concurrent programming. It combines the powerful features of Lisp, a long-standing family of programming languages known for its flexibi…

1
Caffe: A Deep Learning Framework for Speed and Modularity 3:18

4d ago3:18

3:18

Caffe is an open-source deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and contributed to by a global community of researchers and engineers. Designed with an emphasis on speed, modularity, and ease of use, Caffe is particularly well-suited for developing and deploying deep learning models, especially in the fie…

1
Nimfa: A Python Library for Non-negative Matrix Factorization 5:43

40m ago5:43

5:43

Nimfa is a Python library specifically designed for performing Non-negative Matrix Factorization (NMF), a powerful technique used in data analysis to uncover hidden structures and patterns in non-negative data. Developed to be both flexible and easy to use, Nimfa provides a comprehensive set of tools for implementing various NMF algorithms, making …

1
Mingle JS - Use React or Vue components in Livewire with Patricio 35:20

1h ago35:20

35:20

We are joined by @PatricioOnCode to talk about Mingle JS which allows you to mix React and Vue components in Livewire. EPISODE LINKS: * Mingle JS https://minglejs.unitedbycode.com * PHP WASM https://www.youtube.com/watch?v=L-MAzsDm5d0 * Play with Laravel, save the code, and share it with others https://github.com/ijpatricio/playwithlaravel * VoxPop…

1
FastAPI: High-Performance Web Framework for Modern APIs 6:30

1h ago6:30

6:30

FastAPI is a modern, open-source web framework for building APIs with Python. Created by Sebastián Ramírez, FastAPI is designed to provide high performance, easy-to-use features, and robust documentation. It leverages Python's type hints to offer automatic data validation and serialization, making it an excellent choice for developing RESTful APIs …

1
Remote pairing around rounding errors with a pint 52:42

1h ago52:42

52:42

In this episode, Jake and Michael discuss (inadvertently) bathing keyboards, pairing with remote colleagues and friends, using rational numbers to deal with rounding errors (sort of), and running code style fixers in CI or as a pre-commit hook. Show links Tuple Laramates Around brick/math brick/money Pint Running Pint on GitHub Actions Husky Whisky…

1
Signals 26:17

5d ago26:17

26:17

It was teased in the last episode already and here it - Michael and Alex talk about the current hype in the front end development community: Signals. But if you as a Vue developer don't feel hyped around it and maybe even didn't hear much around it, fear no more - that is normal and will be explained in the episode too. Join the two Vue experts cov…

1
NetBeans: A Comprehensive Integrated Development Environment 4:23

2h ago4:23

4:23

NetBeans is a powerful, open-source integrated development environment (IDE) used by developers to create applications in various programming languages. Initially developed by Sun Microsystems and now maintained by the Apache Software Foundation, NetBeans provides a robust platform for building desktop, web, and mobile applications. It supports a w…

1
Area Under the Curve (AUC): A Comprehensive Metric for Evaluating Classifier Performance 5:24

3d ago5:24

5:24

The Area Under the Curve (AUC) is a widely used metric in the evaluation of binary classification models. It provides a single scalar value that summarizes the performance of a classifier across all possible threshold values, offering a clear and intuitive measure of how well the model distinguishes between positive and negative classes. The AUC is…

1
Non-Negative Matrix Factorization (NMF): Uncovering Hidden Patterns in Data 7:43

8d ago7:43

7:43

Non-Negative Matrix Factorization (NMF) is a powerful technique in the field of data analysis and machine learning used to reduce the dimensionality of data and uncover hidden patterns. Unlike other matrix factorization methods, NMF imposes the constraint that the matrix elements must be non-negative. This constraint makes NMF particularly useful f…

1
Signal Detection Theory (SDT): Understanding Decision-Making in the Presence of Uncertainty 4:51

4h ago4:51

4:51

Signal Detection Theory (SDT) is a framework used to analyze and understand decision-making processes in situations where there is uncertainty. Originating in the fields of radar and telecommunications during World War II, SDT has since been applied across various domains, including psychology, neuroscience, medical diagnostics, and market research…

1
AngularJS: Revolutionizing Web Development with Dynamic Applications 5:57

10d ago5:57

5:57

AngularJS is a powerful JavaScript-based open-source front-end web framework developed by Google. Introduced in 2010, AngularJS was designed to simplify the development and testing of single-page applications (SPAs) by providing a robust framework for client-side model–view–controller (MVC) architecture. It has significantly transformed the way dev…

1
Expectation-Maximization Algorithm (EM): A Powerful Tool for Data Analysis 4:24

11d ago4:24

4:24

The Expectation-Maximization (EM) algorithm is a widely-used statistical technique for finding maximum likelihood estimates in the presence of latent variables. Developed by Arthur Dempster, Nan Laird, and Donald Rubin in 1977, the EM algorithm provides an iterative method to handle incomplete data or missing values, making it a cornerstone in fiel…

1
Git Hooks Made Easy: How Whisky Helps Developers with Len Woodward 24:39

4d ago24:39

24:39

We talk with Len Woodward about his project Whisky. Whisky is the simplest, framework-agnostic, CLI tool for managing and enforcing a php project's git hooks across an entire team. Show Links: * [Len's GitHub](https://github.com/ProjektGopher) * [Len's Website](https://LenWoodward.com) * [Len's Twitter](https://x.com/ProjektGopher) * [Len's YouTube…

1
Kotlin: A Modern Programming Language for the JVM and Beyond 7:05

2h ago7:05

7:05

Kotlin is a contemporary programming language developed by JetBrains, designed to be fully interoperable with Java while offering a more concise and expressive syntax. Introduced in 2011 and officially released in 2016, Kotlin has rapidly gained popularity among developers for its modern features, safety enhancements, and seamless integration with …

1
Reactivity in Vue 42:01

14d ago42:01

42:01

Join Alex and Michael on a talk about a key topic in Vue.js - the reactivity system. Before diving into how it works in Vue 3, reactivity in Vanilla JS is covered. Then, the differences between the major Vue versions are discussed, showing an astonishing evolution in terms of DX but also performance when it comes to reactivity. Of course, the ref v…

1
Dynamic Topic Models (DTM): Capturing the Evolution of Themes Over Time 5:00

14d ago5:00

5:00

Dynamic Topic Models (DTM) are an advanced extension of topic modeling techniques designed to analyze and understand how topics in a collection of documents evolve over time. Developed to address the limitations of static topic models like Latent Dirichlet Allocation (LDA), DTMs allow researchers and analysts to track the progression and transforma…

1
False Positive Rate (FPR): A Critical Metric for Evaluating Classification Accuracy 6:14

16d ago6:14

6:14

The False Positive Rate (FPR) is a crucial metric used to evaluate the performance of binary classification models. It measures the proportion of negative instances that are incorrectly classified as positive by the model. Understanding FPR is essential for assessing how well a model distinguishes between classes, particularly in applications where…

1
We Can't Talk About Anything 1:42:30

25m ago1:42:30

1:42:30

Things are in full swing. There are many things we cannot say. We are both slammed trying to get everything done for Laracon. Which led to this not being put out very quickly.By Daniel Coulbourne & Caleb Porzio

1
False Negative Rate (FNR): Understanding Missed Predictions in Classification Models 5:42

16h ago5:42

5:42

The False Negative Rate (FNR) is a critical metric used to evaluate the performance of binary classification models, particularly in applications where failing to identify positive instances can have significant consequences. FNR measures the proportion of actual positive instances that are incorrectly classified as negative by the model. This metr…

1
True Positive Rate (TPR): A Key Metric for Assessing Classifier Performance 8:00

1d ago8:00

8:00

The True Positive Rate (TPR), also known as sensitivity or recall, is a fundamental metric used to evaluate the performance of binary classification models. TPR measures the proportion of actual positive instances that are correctly identified by the model, making it crucial for applications where correctly identifying positive cases is essential, …

1
Law of Large Numbers (LLN): The Principle Behind Consistent Averages 3:58

12d ago3:58

3:58

The Law of Large Numbers (LLN) is a fundamental concept in probability theory and statistics that describes how the average of a large number of trials converges to the expected value as the number of trials increases. Essentially, the LLN guarantees that as a sample size grows, the sample mean will get closer and closer to the population mean, pro…

1
True Negative Rate (TNR): A Critical Metric for Evaluating Classifier Performance 4:51

4d ago4:51

4:51

The True Negative Rate (TNR), also known as specificity, is a crucial metric in the evaluation of binary classification models. TNR measures the proportion of actual negative instances that are correctly identified by the model. It is particularly important in applications where accurately identifying negative cases is as critical as identifying po…

1
Matthews Correlation Coefficient (MCC): A Robust Metric for Evaluating Binary Classifiers 5:30

4d ago5:30

5:30

The Matthews Correlation Coefficient (MCC) is a comprehensive metric used to evaluate the performance of binary classification models. Named after British biochemist Brian W. Matthews, MCC takes into account true and false positives and negatives, providing a balanced measure even when classes are imbalanced. It is particularly valued for its abili…

1
Building Desktop Applications using Native PHP with Simon Hamp 33:15

4d ago33:15

33:15

In this episode, we are joined by Simon Hamp, the creator of Native PHP, about the project and its potential. Native PHP is a tool that allows developers to build desktop applications using PHP and distribute them without requiring PHP on the user's machine. Show Links: * NativePHP * Cronikl * Awesome NativePHP * LaraDir…

1
Receiver Operating Characteristic (ROC) Curve: A Key Tool for Evaluating Classification Models 5:19

11d ago5:19

5:19

The Receiver Operating Characteristic (ROC) curve is a fundamental tool used in the evaluation of classification models. It is particularly useful for assessing the performance of binary classifiers by visualizing the trade-offs between true positive rates and false positive rates at various threshold settings. The ROC curve provides a comprehensiv…

1
The one with environment config 40:15

5d ago40:15

40:15

In this episode, Jake and Michael discuss different approaches to configuring a Laravel app, for consistency, security, and shareability among a team and across environments. Show links Australian men on the phone to each other Go ahead, delete your .env.example fileBy Jacob Bennett and Michael Dyrynda

1
Documentation and Migration: From Vue 2 to Vue 3 (with Natalia Tepluhina) 1:21:57

22d ago1:21:57

1:21:57

For the 20th episode we surprise you with a "in-person" podcast episode! Alex is joined by Principal Engineer and Vue Core Team Member Natalia Tepluhina to talk about two important topics - Documentation and the Migration from Vue 2 to Vue 3. Learn in this episode what Natalia does in the core team, how difficult writing docs is and how to improve …

1
Correlated Topic Model (CTM): Enhancing Topic Modeling with Correlation Structures 6:16

19d ago6:16

6:16

The Correlated Topic Model (CTM) is an advanced probabilistic model developed to address the limitations of traditional topic modeling techniques like Latent Dirichlet Allocation (LDA). Introduced by David Blei and John Lafferty in 2006, CTM enhances topic modeling by capturing correlations between topics, providing a more nuanced and realistic rep…

1
Tanh (Hyperbolic Tangent): A Widely-Used Activation Function in Neural Networks 5:26

7d ago5:26

5:26

The Tanh (Hyperbolic Tangent), is a widely-used activation function in neural networks. Known for its S-shaped curve, the Tanh function maps any real-valued number to a range between -1 and 1, making it a symmetric function around the origin. This symmetry makes it particularly effective for neural networks, providing both positive and negative out…

1
Behind the Mic: Adam Gordon Bell on Communication with Software Misadventures Podcast 1:03:40

7d ago1:03:40

1:03:40

Today the tables have turned and you're going to hear someone interview me. Ronak and Guang from the Software Misadventures podcast are going to interview me about podcasting. My history as a software developer and I guess this big idea. That I don't think I've shared too much about the importance of communication. More details including a video ve…

1
Sigmoid Function: The Key to Smooth, Non-Linear Activation in Neural Networks 4:24

8d ago4:24

4:24

The sigmoid function is a fundamental mathematical function used extensively in machine learning, particularly in the context of neural networks. Its characteristic S-shaped curve makes it ideal for scenarios requiring smooth, non-linear transitions. Core Features of the Sigmoid Function Smooth Non-Linearity: The sigmoid function introduces smooth …

1
Deep LIME (DLIME): Bringing Interpretability to Deep Learning Models 4:00

9d ago4:00

4:00

Deep LIME (DLIME) is an advanced adaptation of the original LIME (Local Interpretable Model-agnostic Explanations) framework, specifically designed to provide interpretability for deep learning models. As deep learning models become increasingly complex and widely used, understanding their decision-making processes is critical for building trust, e…

1
LIME-SUP (LIME for Sequential and Unsupervised Problems): Extending Interpretability to Complex Models 5:42

10d ago5:42

5:42

LIME-SUP, short for Local Interpretable Model-agnostic Explanations for Sequential and Unsupervised Problems, is an advanced extension of the LIME framework. Developed to address the interpretability challenges in sequential and unsupervised machine learning models, LIME-SUP provides insights into how these complex models make predictions and gener…

1
SHAP (SHapley Additive exPlanations): Unveiling the Inner Workings of Machine Learning Models 4:18

11d ago4:18

4:18

SHAP, short for SHapley Additive exPlanations, is a unified framework designed to interpret the predictions of machine learning models. Developed by Scott Lundberg and Su-In Lee, SHAP leverages concepts from cooperative game theory, particularly the Shapley value, to provide consistent and robust explanations for model predictions. By attributing e…

1
Built With Laravel featuring Matt Stauffer 24:00

11d ago24:00

24:00

Today, Matt Stauffer joined us to discuss his newest project, BuiltWithLaravel, a list of companies and organizations using Laravel in the non-Laravel world. This is the list to use when you want to show someone how widespread Laravel's adoption is. Show links * BuiltWithLaravel: https://builtwithlaravel.com * Tighten: https://tighten.com/ * Fieldg…

1
LIME (Local Interpretable Model-agnostic Explanations): Demystifying Machine Learning Models 8:10

12d ago8:10

8:10

LIME, short for Local Interpretable Model-agnostic Explanations, is a technique designed to provide interpretability to complex machine learning models. Developed by researchers Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin, LIME helps understand and trust machine learning models by explaining their predictions. It is model-agnostic, meani…

1
Nuxt Tips You Have To Know 43:37

22d ago43:37

43:37

Are you using Nuxt and want to hear some insights you weren't aware of? Perfect! Then this DejaVue podcast episode is what you need. Michael and Alex are going through more than five big tips around Nuxt, from features under the radar over to a big chunk of amazing benefits and why they exist, all from Michael's Nuxt Tips Collection* which releases…

1
GPT-4o: The Next Generation of AI Language Models 4:31

13d ago4:31

4:31

GPT-4o, short for Generative Pre-trained Transformer 4 O, is the latest iteration of OpenAI's groundbreaking series of language models. Building upon the success of its predecessors, GPT-4o brings significant advancements in natural language understanding and generation. This state-of-the-art model continues to push the boundaries of what artificia…

1
SimCLR: Simple Framework for Contrastive Learning of Visual Representations 5:00

14d ago5:00

5:00

SimCLR (Simple Framework for Contrastive Learning of Visual Representations) is a pioneering approach in the field of self-supervised learning, designed to leverage large amounts of unlabeled data to learn useful visual representations. Developed by researchers at Google Brain, SimCLR simplifies the process of training deep neural networks without …

Podcasts Worth a Listen

Vuejs Podcasts

Podcasts Worth a Listen

Quick Reference Guide