ML Fundamentals

Dave Selinger — AI and the Next Generation of Security Systems

Waste Classification Machine Learning Classification Project-Waste Recycling

CycleGAN Paper Walkthrough

Code With Me : Logistic Regression (from scratch) !

[AI Access] Applied Analytics from End-to-End

L10.5.4 Dropout in PyTorch

L10.5.3 (Optional) Dropout Ensemble Interpretation

Building World-Class NLP Models with Transformers and Hugging Face | Grandmaster Series E4

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Directions in ML: Taking Advantage of Randomness in Expensive Optimization Problems

AI and Gaming Research Summit 2021 - Understanding Players (Day 2 Track 1.2)

Expectations with Machine Learning

PyTorch Time Sequence Prediction With LSTM - Forecasting Tutorial

Level up your software engineering skills as a data scientist | ML Monthly February 2021

Neural Networks Part 8: Image Classification with Convolutional Neural Networks (CNNs)

Machine Learning Frameworks - The Landscape

How to Learn DATA SCIENCE Ridiculously FAST

Python Tutorial for Beginners - Learn Python in 5 Hours [FULL COURSE]

PIE & AI Kigali – Building a Career in Data Science: From Learning to Landing a Job

Cal Newport: Deep Work, Focus, Productivity, Email, and Social Media | Lex Fridman Podcast #166

Intro to Deep Learning (ML Tech Talks)

Does anyone know of a good way to manage dependencies? // MLOps Coffee Sessions #31 Part 2 Clip

Live AWS For Data Science - Deploying Machine Learning Application In EC2 Instance

Radial Basis Function Kernel : Data Science Concepts

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Autoencoders in Python with Tensorflow/Keras

Metric Learning for Images - Keras Code Examples

L10.5.2 Dropout Co-Adaptation Interpretation

L10.5.1 The Main Concept Behind Dropout

L10.4 L2 Regularization for Neural Nets

L10.3 Early Stopping

L10.2 Data Augmentation in PyTorch

L10.1 Techniques for Reducing Overfitting

L10.0 Regularization Methods for Neural Networks -- Lecture Overview

How (and why) you should undervolt your GPU - A step by step guide (Deep Learning/Gaming/Mining)

L9.5.2 Custom DataLoaders in PyTorch --Code Example

L9.5.1 Cats & Dogs and Custom Data Loaders

L9.4 Overfitting and Underfitting

Pix2Pix Paper Walkthrough

Amazing Data Science End To End Project From Starters In ML and Deep Learning- Agriculture Domain

L9.3.3 Multilayer Perceptron in PyTorch -- Code Example Part 3/3 (Script Setup)

L9.3.2 Multilayer Perceptron in PyTorch -- Code Example Part 2/3 (Jupyter Notebook)

L9.3.1 Multilayer Perceptron -- Code Example Part 1/3 (Slide Overview)

L9.2 Nonlinear Activation Functions

L9.1 Multilayer Perceptron Architecture

L9.0 Multilayer Perceptrons -- Lecture Overview

Outliers : Data Science Basics

Monday Night Live Q&A - Ask Anything Related To Data Science