ML Fundamentals

7.1: Machine Learning as a Web Engineer - putting knowledge into practice

Toxicity Classifier Streamlit App

Motion interactive AR with Rotoflo - Made with TensorFlow.js

AWS ML Heroes in 15: Geospatial ML with Amazon SageMaker- AWS Machine Learning in 15

6.5: Dealing with edge cases in spam detection

Front End vs Back End - Which one is good for you ? | Entri Elevate

How to Build a Full-Stack Recommender System

The Importance of Connecting Data Science Projects to Business Goals

C4AI Sparks: Rosanne Liu on Career Creation for Non-Standard Candidates

Can We Earn More From FreeLancing Than Full time Jobs? Steps To Start Your Free Lancing Career

Evolution of Infrastructure in Machine Learning // Simon Thompson // MLOps Shorts

Legacy Code Conversion - Computerphile

PyTorch Lightning #1 - Why Lightning?

The Confusion Matrix : Data Science Basics

Mathematics required for Data Science? | Machine Learning #shorts

What is MLOps and how to get started? | MLOps series

Team Codebasics UNITED 🔥🎇

Outerbounds Live Stream

Google Cloud Retail Search and Browse Console deep dive

Deploying Models for Sentiment Analysis on Cloud | DataHour by Prashant Sahu

Visualize a Neural Net Learning Polynomial Functions

DO NOT start your MACHINE LEARNING journey like this...

🔴 LIVE 🔴 Studying Recommender Systems

TensorFlow.js Community "Show & Tell" #9

Multi Head Attention in Transformer Neural Networks with Code!

The Most Important Curve in Data Science

Zero to Hero Programmer in 4 Steps | Entri Elevate

6.6: Using a retrained spam detection model in the web browser with TensorFlow.js

6.1: Using models from Python in the web browser with TensorFlow.js

6.2: Converting Python saved models with the TensorFlow.js command line converter

Recognize custom objects with TensorFlow.js.

5.3: Using layers models for transfer learning

5.1: Transfer learning: Retraining existing models in the web browser with TensorFlow.js

This is what we mean when we say Google Developer Experts (GDE)

🔴 LIVE 🔴 Studying Recommender Systems (pt. 2)

4.7.2: Beyond perceptrons: Convolutional Neural Network (CNNs) - Implementation with TensorFlow.js

4.7.1: Beyond perceptrons: Convolutional Neural Network (CNNs) in the web browser

4.6.2: Multi-layer perceptrons for classification - Implementing a classifier in TensorFlow.js

ML tutorial: How to solve classification problems with TensorFlow and multi-layer perceptrons

4.5.2: Multi-layer perceptrons - Deep neural networks for non linear data

4.5.1: Multi-layer perceptrons - The limits of a single neuron

TensorFlow.js tutorial: A neuron implementation for linear regression

4.4.2: Implement a neuron for linear regression - Importing and normalizing training data

4.4.1: Implement a neuron for linear regression - Training data and outliers

ML tutorial: How to train neurons

4.3.1: What's a neuron?

4.2: Gathering, refining, and using data effectively for ML model datasets

The Challenges of Integrating Multiple Tasks into One Model in MLOps // Ethan Rosenthal