ML Fundamentals

How mlctl Helps Intuit's Workflow // Srivathsan Canchi // Coffee Sessions # 50 short clip

Newton’s fractal (which Newton knew nothing about)

Create feature interactions using PolynomialFeatures

Data Selection for Data-Centric AI: Data Quality Over Quantity // Cody Coleman //Coffee Sessions#59

PyTorch Book Reading - 7. Training a Tumor classifier

How Al is Changing Marketing and SEO (And How to Use it In Your Business)

UIUC's Online Master's in Computer Science MCS & MCS-DS Degrees Webinar

Speed up GridSearchCV using parallel processing

Grokking: Generalization beyond Overfitting on small algorithmic datasets (Paper Explained)

1. Introduction and Matrix Multiplication

Introducing the first Women in Machine Learning Symposium

Rebecca Fiebrink - Creative AI Conversations

The problem with percentages ... and the simple equation to solve it

TensorFlow for Computer Vision Course - Full Python Tutorial for Beginners

PyTorch Book Reading - 6. Working CT Scan Data in PyTorch, Classifying Tumours.

Perform Easy EDA And Generate Python Using Mito

Machine Learning Model Deployment with Python (Streamlit + MLflow) | Part 2/2

What is Hypothesis Testing ? Math, Statistics for data science, machine learning

TensorFlow.js Community "Show & Tell" #6

Build a Deep Facial Recognition App // Part 5 - Training a Siamese Neural Network // #Python

Machine Learning Model Deployment with Python (Streamlit + MLflow) | Part 1/2

Deep learning project end to end | Potato Disease Classification - 8 : Mobile App in React Native

Jeffrey Shainline: Neuromorphic Computing and Optoelectronic Intelligence | Lex Fridman Podcast #225

Talks S2E7 (Konrad Banachewicz): Time Series Analysis - Vintage Toolkit For Modern Times

Time Series Forecasting Made Easy Using Dart Library - Perform Multivariate Forecasting In No Time

Gies College of Business Webinar: From MOOCs to Master's

Build a Deep Facial Recognition App // Part 4 - Building a Siamese Neural Network // #Python

#71 Scaling Machine Learning Adoption: A Pragmatic Approach (with Noah Gift)

Jay McClelland: Neural Networks and the Emergence of Cognition | Lex Fridman Podcast #222

Introduction to Generative Adversarial Networks (Tutorial Recording at ISSDL 2021)

Talks S2E6 (Louise Ferbach): Deep Learning For Survival Analysis

A Truly Unbiased Model

10 Types of Features your Location ML Model is Missing // Anne Cocos // Coffee Sessions #58

Use OrdinalEncoder instead of OneHotEncoder with tree-based models

Three Categories of SGT // Alex Chung // Coffee #50 short clip

Chai Time Kaggle Talks with Andrada Olteanu - EDA Grandmastery

Detecting model misbehavior with W&B

Drop the first category from binary features (only) with OneHotEncoder

Managing Outcomes Generated by Data Scientists // Stefan Krawczyk // Coffee Sessions #49 short clip

Importance of Platform // Julien Chaumond // Coffee Sessions #48 short clip

Engineering Best Practices for Machine Learning // Alex Serban // MLOps Meetup #79

Estimators only print parameters that have been changed

Chris Albon — ML Models and Infrastructure at Wikimedia

W&B Fastbook Reading Group — 15. Application Architectures Deep Dive

Load a toy dataset into a DataFrame

PyTorch Book Reading - 4. Train your first CNN using Torch

Career Gap and Now a Machine Learning Engineer At Sony

Machine Learning Projects You NEVER Knew Existed