Канал: Ricardo Calix

Old 2011 talk - I was working on a type of generative AI actually (more like emotions and NLP)

Old 2011 talk - I was working on a type of generative AI actually (more like emotions and NLP)

Direct Preference Optimization (DPO) - math insight explained

Direct Preference Optimization (DPO) - math insight explained

100+ Essential Linear Algebra Operations for Deep Learning: A Cheat Sheet and Workbook

100+ Essential Linear Algebra Operations for Deep Learning: A Cheat Sheet and Workbook

Brief Contrast of CNNs and Transfer Learning: LeNet, AlexNet, VGGs, ResNets and more

Brief Contrast of CNNs and Transfer Learning: LeNet, AlexNet, VGGs, ResNets and more

Residuals - Your own ResNet from Scratch, and Fine-tuning a pre-trained ResNet 18 (In PyTorch)

Residuals - Your own ResNet from Scratch, and Fine-tuning a pre-trained ResNet 18 (In PyTorch)

Cross Entropy and Gradients

Cross Entropy and Gradients

GPU issues and CIFAR-10 challenge with PyTorch

GPU issues and CIFAR-10 challenge with PyTorch

Linux and BASH miscellaneous scripting (part 2)

Linux and BASH miscellaneous scripting (part 2)

Linux and BASH - Mail scripting (part 3)

Linux and BASH - Mail scripting (part 3)

Transfer Learning with Torchvision models: AlexNet, ResNet, and more

Transfer Learning with Torchvision models: AlexNet, ResNet, and more

GANs with fastai and Art Style Transfer with PyTorch

GANs with fastai and Art Style Transfer with PyTorch

Linux and BASH scripting (part 1)

Linux and BASH scripting (part 1)

The MSE loss function for machine learning

The MSE loss function for machine learning

PyTorch and the CIFAR-10 challenge (part 3)

PyTorch and the CIFAR-10 challenge (part 3)

Linux with GREP, AWK, and Find

Linux with GREP, AWK, and Find

PyTorch and the CIFAR-10 challenge (part 2)

PyTorch and the CIFAR-10 challenge (part 2)

Network GeoLocation with Python and Linux

Network GeoLocation with Python and Linux

Conditional Generative Adversarial Networks (CGANs) from scratch with PyTorch

Conditional Generative Adversarial Networks (CGANs) from scratch with PyTorch

Generative Adversarial Networks (GANs) from scratch with PyTorch

Generative Adversarial Networks (GANs) from scratch with PyTorch

PyTorch and the CIFAR-10 challenge (part 1)

PyTorch and the CIFAR-10 challenge (part 1)

Linux and the Simple Network Management Protocol (SNMP) - part 3

Linux and the Simple Network Management Protocol (SNMP) - part 3

Training a deep learning model with PyTorch for the Iris dataset (part 2)

Training a deep learning model with PyTorch for the Iris dataset (part 2)

Object Detection with YOLO - detecting watermelons

Object Detection with YOLO - detecting watermelons

Training a deep learning model with PyTorch for the Iris dataset (part 1)

Training a deep learning model with PyTorch for the Iris dataset (part 1)

Linux and the Simple Network Management Protocol (SNMP) - part 1

Linux and the Simple Network Management Protocol (SNMP) - part 1

Linux and the Simple Network Management Protocol (SNMP) - part 2

Linux and the Simple Network Management Protocol (SNMP) - part 2

Introduction to MapReduce and the Linux command line pipeline (part 2)

Introduction to MapReduce and the Linux command line pipeline (part 2)

Fine-Tune an image classifier with your own data, ResNet, and Fastai

Fine-Tune an image classifier with your own data, ResNet, and Fastai

Linking PyTorch nn.linear() to y = w*x + b

Linking PyTorch nn.linear() to y = w*x + b

Introduction to MapReduce and the Linux command line pipeline (part 1)

Introduction to MapReduce and the Linux command line pipeline (part 1)

The duality of Neural Networks and the Matrix Multiplication

The duality of Neural Networks and the Matrix Multiplication

Netcat and the UFW Linux firewall

Netcat and the UFW Linux firewall

Foundations of Neural Networks for Computer Vision with fastai

Foundations of Neural Networks for Computer Vision with fastai

Showcase of fastai example capabilitites

Showcase of fastai example capabilitites

A light history and introduction to Neural Networks

A light history and introduction to Neural Networks

Linux and the UFW firewall

Linux and the UFW firewall

A KNN only Conditional Generative Model with Numpy and PyScript - Annotation (part 2)

A KNN only Conditional Generative Model with Numpy and PyScript - Annotation (part 2)

Linux user account management

Linux user account management

The HuggingFace TRL Library and an Example for Reinforcement Learning Through Human Feedbacks

The HuggingFace TRL Library and an Example for Reinforcement Learning Through Human Feedbacks

Basic Ideas of Reinforcement Learning Through Human Feedbacks (RLHF)

Basic Ideas of Reinforcement Learning Through Human Feedbacks (RLHF)

A KNN only Conditional Generative Model with Numpy and PyScript (part 1)

A KNN only Conditional Generative Model with Numpy and PyScript (part 1)

Linux and DNS Attacks

Linux and DNS Attacks

KNN and performance metrics with Numpy and SKLearn

KNN and performance metrics with Numpy and SKLearn

Fine Tune pre-trained GPT and BERT models with the Huggingface library

Fine Tune pre-trained GPT and BERT models with the Huggingface library

Linux, scapy, and network sniffing and spoofing

Linux, scapy, and network sniffing and spoofing

The simple linear algebra for Attention, GPTs, BERTs, and Full Transformers in PyTorch (part 5)

The simple linear algebra for Attention, GPTs, BERTs, and Full Transformers in PyTorch (part 5)

Fine-Tuning HF examples on GPU Scholar, scratch disk space

Fine-Tuning HF examples on GPU Scholar, scratch disk space

The Euclidean Distance and KNN in Numpy

The Euclidean Distance and KNN in Numpy

Linux and DNS

Linux and DNS

A simple generative ML model with just KNN

A simple generative ML model with just KNN

Linux command pipeline examples

Linux command pipeline examples

Embeddings, GPTs, BERTs, Full Transformers, in PyTorch (Part 4)

Embeddings, GPTs, BERTs, Full Transformers, in PyTorch (Part 4)

GPU Scholar cloud, GPTs, BERTs, Full Transformers, in PyTorch (Part 3)

GPU Scholar cloud, GPTs, BERTs, Full Transformers, in PyTorch (Part 3)

ML pipeline with Pandas and Sklearn

ML pipeline with Pandas and Sklearn

Linux and Crontab

Linux and Crontab

GPTs, BERTs, Full Transformers, in PyTorch (Part 2)

GPTs, BERTs, Full Transformers, in PyTorch (Part 2)

GPTs, BERTs, Full Transformers, in PyTorch (Part 1)

GPTs, BERTs, Full Transformers, in PyTorch (Part 1)

WEKA for classification and regression

WEKA for classification and regression

The UNIX Way (Linux file modes, access control, chmod, links, SETUID)

The UNIX Way (Linux file modes, access control, chmod, links, SETUID)

Getting Started with Numpy (matrices, concatenation and stacking, math, Broadcasting, masks, etc.)

Getting Started with Numpy (matrices, concatenation and stacking, math, Broadcasting, masks, etc.)

Linux Systems admin with Python (dictionaries, lists, password cracking and the Cuckoo's Egg

Linux Systems admin with Python (dictionaries, lists, password cracking and the Cuckoo's Egg

A simple example and discussion of how ChatGPT was trained (with RLHF and HuggingFace)

A simple example and discussion of how ChatGPT was trained (with RLHF and HuggingFace)

Hugging Face Zero Shot BERT classifier

Hugging Face Zero Shot BERT classifier

HuggingFace simple BERT examples

HuggingFace simple BERT examples

Getting Started with Numpy (Anaconda, numpy arrays, matrices, indexing, slicing, reshaping, etc.)

Getting Started with Numpy (Anaconda, numpy arrays, matrices, indexing, slicing, reshaping, etc.)

Python for Linux Systems Admin (subprocess, os, socket, and making a basic port scanner)

Python for Linux Systems Admin (subprocess, os, socket, and making a basic port scanner)

How to convert any problem into a machine learning problem

How to convert any problem into a machine learning problem

Basic Linux commands everyone should know

Basic Linux commands everyone should know

Starting with GPTs (A Hello World Example)

Starting with GPTs (A Hello World Example)

Intro to Reinforcement Learning through Human Feedbacks (RLHF)

Intro to Reinforcement Learning through Human Feedbacks (RLHF)

Welcome to ITS 530 - DL, RLHF, and Transfer Learning (Spring 2024)

Welcome to ITS 530 - DL, RLHF, and Transfer Learning (Spring 2024)

ITS 372 - Navigating the Linux File System with ls, cd, and pwd

ITS 372 - Navigating the Linux File System with ls, cd, and pwd

Welcome to ITS 372 - System Admin in Linux

Welcome to ITS 372 - System Admin in Linux

Welcome to ITS 365 Machine Learning Foundations (Spring 2024)

Welcome to ITS 365 Machine Learning Foundations (Spring 2024)

Machine Learning for Cyber Security - Naive Bayes

Machine Learning for Cyber Security - Naive Bayes

Machine Learning for Cyber Security - Malware Introduction

Machine Learning for Cyber Security - Malware Introduction

Machine Learning for Cyber Security - Performance Metrics

Machine Learning for Cyber Security - Performance Metrics

Machine Learning for Cyber Security - IOT Device Detection Introduction

Machine Learning for Cyber Security - IOT Device Detection Introduction

Machine Learning for Cyber Security - KNN

Machine Learning for Cyber Security - KNN

Machine Learning for Cyber Security - Data for Deep Learning

Machine Learning for Cyber Security - Data for Deep Learning

Machine Learning for Cyber Security - Data for Deep Learning

Machine Learning for Cyber Security - Data for Deep Learning

Machine Learning for Cyber Security - IOT Device Detection Weka

Machine Learning for Cyber Security - IOT Device Detection Weka

Machine Learning for Cyber Security - Linear to Logistic Regression

Machine Learning for Cyber Security - Linear to Logistic Regression

Machine Learning for Cyber Security - Course Introduction

Machine Learning for Cyber Security - Course Introduction

Machine Learning for Cyber Security - Malware ML

Machine Learning for Cyber Security - Malware ML

Machine Learning for Cyber Security - Clustering

Machine Learning for Cyber Security - Clustering

Machine Learning for Cyber Security - Phishing Lab Introduction

Machine Learning for Cyber Security - Phishing Lab Introduction

Machine Learning for Cyber Security - Separate Files Loading

Machine Learning for Cyber Security - Separate Files Loading

Machine Learning for Cyber Security - Linear Regression in Tensorflow

Machine Learning for Cyber Security - Linear Regression in Tensorflow

Machine Learning for Cyber Security - Logistic Regression in Tensorflow

Machine Learning for Cyber Security - Logistic Regression in Tensorflow

Machine Learning for Cyber Security - Datasets and Features

Machine Learning for Cyber Security - Datasets and Features

Machine Learning for Cyber Security - Malware Feature Extraction

Machine Learning for Cyber Security - Malware Feature Extraction

Machine Learning for Cyber Security - Malware in Weka

Machine Learning for Cyber Security - Malware in Weka

Machine Learning for Cyber Security - IOT Device Detection Coding Part

Machine Learning for Cyber Security - IOT Device Detection Coding Part

Machine Learning for Cyber Security - KDD in Tensorflow using GPU

Machine Learning for Cyber Security - KDD in Tensorflow using GPU

Machine Learning for Cyber Security - Malware Sklearn

Machine Learning for Cyber Security - Malware Sklearn

Machine Learning for Cyber Security - Deep Neural Networks

Machine Learning for Cyber Security - Deep Neural Networks

Machine Learning for Cyber Security - Deep Learning Intro

Machine Learning for Cyber Security - Deep Learning Intro

Machine Learning for Cyber Security - sklearn

Machine Learning for Cyber Security - sklearn

Machine Learning for Cyber Security - Logistic Regression (version 2)

Machine Learning for Cyber Security - Logistic Regression (version 2)

Machine Learning for Cyber Security - Weka

Machine Learning for Cyber Security - Weka

Implementing a simple GPT in PyTorch (Take Two)

Implementing a simple GPT in PyTorch (Take Two)

Cryptography Scavenger Hunt 2023

Cryptography Scavenger Hunt 2023

Conditional GANs (CGANs) and MNIST in PyTorch from scratch

Conditional GANs (CGANs) and MNIST in PyTorch from scratch

Implementing a simple GPT in PyTorch

Implementing a simple GPT in PyTorch

What are Transformers and GPTs?

What are Transformers and GPTs?

High overview of the original Transformer architecture for Large Language Models

High overview of the original Transformer architecture for Large Language Models

GANs Generator and Discriminator losses and training

GANs Generator and Discriminator losses and training

A client-server demonstration of Public Key Infrastructure with openssl

A client-server demonstration of Public Key Infrastructure with openssl

A Simple Generative Adversarial Network (GAN) in PyTorch

A Simple Generative Adversarial Network (GAN) in PyTorch

MNIST classification with CNNs in PyTorch (part 1)

MNIST classification with CNNs in PyTorch (part 1)

MNIST classification with CNNs in PyTorch (part 2)

MNIST classification with CNNs in PyTorch (part 2)

PyCrypto Dome: RSA Encryption, Decryption, and Digital Signatures

PyCrypto Dome: RSA Encryption, Decryption, and Digital Signatures

Speed test between RSA and AES ciphers

Speed test between RSA and AES ciphers

Intuition of Convolutions in Convolutional Neural Networks

Intuition of Convolutions in Convolutional Neural Networks

Intuition of Cross Entropy and Performance metrics for Classification in machine learning

Intuition of Cross Entropy and Performance metrics for Classification in machine learning

A contrast of Neural Network architectures, losses, inference functions, and activation functions

A contrast of Neural Network architectures, losses, inference functions, and activation functions

PyCrypto Dome: Hash functions and AES

PyCrypto Dome: Hash functions and AES

A simple Certificate Authority to digitally sign Alice's Public Key

A simple Certificate Authority to digitally sign Alice's Public Key

CIFAR10 classification with PyTorch and performance metrics

CIFAR10 classification with PyTorch and performance metrics

Machine Learning basic concepts and Optimization

Machine Learning basic concepts and Optimization

Machine Learning accuracy, precision, recall, f1-measure, confusion matrix

Machine Learning accuracy, precision, recall, f1-measure, confusion matrix

RSA, digital signatures, and certificate authorities

RSA, digital signatures, and certificate authorities

Classification with PyTorch and CIFAR10 (part 2)

Classification with PyTorch and CIFAR10 (part 2)

Classification with PyTorch and CIFAR10 (part 1)

Classification with PyTorch and CIFAR10 (part 1)

WEKA, classification algorithms, and feature ranking

WEKA, classification algorithms, and feature ranking

RSA encrypt and decrypt in Python

RSA encrypt and decrypt in Python

Classification model for CIFAR10 with PyTorch (part 2)

Classification model for CIFAR10 with PyTorch (part 2)

Classification model for CIFAR10 with PyTorch (part 1)

Classification model for CIFAR10 with PyTorch (part 1)

Some RSA details and breaking RSA

Some RSA details and breaking RSA

Deploy PyTorch Regression model to Web with ONNX and GitHub (part 2)

Deploy PyTorch Regression model to Web with ONNX and GitHub (part 2)

Deploy XGBoost Regression model to Web with ONNX runtime and GitHub

Deploy XGBoost Regression model to Web with ONNX runtime and GitHub

Deploy PyTorch Regression model to Web with ONNX and GitHub (part 1)

Deploy PyTorch Regression model to Web with ONNX and GitHub (part 1)

Writing to files and the RSA algorithm in Python

Writing to files and the RSA algorithm in Python

The Iris dataset and classification models with WEKA

The Iris dataset and classification models with WEKA

Deploying XGBoost Models with ONNX runtime and GitHub (part 2)

Deploying XGBoost Models with ONNX runtime and GitHub (part 2)

Deploying XGBoost Models with ONNX runtime and GitHub (part 1)

Deploying XGBoost Models with ONNX runtime and GitHub (part 1)

Deploying PyTorch Regression Models with ONNX and GitHub (part 2)

Deploying PyTorch Regression Models with ONNX and GitHub (part 2)

Python modulo operation for RSA

Python modulo operation for RSA

Deploying PyTorch Regression Models with ONNX and GitHub

Deploying PyTorch Regression Models with ONNX and GitHub

Overview of Regression Trees for Machine Learning

Overview of Regression Trees for Machine Learning

The RSA encryption algorithm and some examples

The RSA encryption algorithm and some examples

Asymmetric Encryption and RSA (continued)

Asymmetric Encryption and RSA (continued)

Asymmetric Encryption and RSA

Asymmetric Encryption and RSA

California Housing Data and XGBoost in Python

California Housing Data and XGBoost in Python

XGBoost python library and performance measurement with the R-square

XGBoost python library and performance measurement with the R-square

Random Forest in WEKA for tabular data

Random Forest in WEKA for tabular data

Python Encryption and Decryption with CBC mode of operation block cipher and XOR (part A)

Python Encryption and Decryption with CBC mode of operation block cipher and XOR (part A)

Python Encryption and Decryption with CBC mode of operation block cipher and XOR (part B)

Python Encryption and Decryption with CBC mode of operation block cipher and XOR (part B)

Regression models with XGBoost (Wine quality dataset)

Regression models with XGBoost (Wine quality dataset)

Regression models with XGBoost (Boston dataset)

Regression models with XGBoost (Boston dataset)

Machine Learning based Regression models with WEKA

Machine Learning based Regression models with WEKA

Object Oriented approach to writing Neural Network architectures with PyTorch

Object Oriented approach to writing Neural Network architectures with PyTorch

Ways to measure the performance of Regression models with Python

Ways to measure the performance of Regression models with Python

The Data Encryption Standard (DES) algorithm (Part A)

The Data Encryption Standard (DES) algorithm (Part A)

The Data Encryption Standard (DES) algorithm (Part B)

The Data Encryption Standard (DES) algorithm (Part B)

A Pseudo Random Number Generator in Python

A Pseudo Random Number Generator in Python

MLP, deep dearning, and other neural network architectures for Regression

MLP, deep dearning, and other neural network architectures for Regression

Standardization and Performance Metrics for Regression

Standardization and Performance Metrics for Regression

Block Ciphers and Round Keys

Block Ciphers and Round Keys

Symmetric Encryption with Stream Ciphers

Symmetric Encryption with Stream Ciphers

Symmetric Encryption modes of operation (ECB and CFB)

Symmetric Encryption modes of operation (ECB and CFB)

Symmetric Encryption modes of operation (CBC)

Symmetric Encryption modes of operation (CBC)

A linear regression model in PyTorch to predict wine quality

A linear regression model in PyTorch to predict wine quality

The Correlation Matrix in Numpy for regression analysis

The Correlation Matrix in Numpy for regression analysis

Loading images with PIL or with PyTorch datasets

Loading images with PIL or with PyTorch datasets

Integrity and Hash functions with openssl

Integrity and Hash functions with openssl

Linear Regression in PyTorch (Part A)

Linear Regression in PyTorch (Part A)

Linear Regression in PyTorch (Part B)

Linear Regression in PyTorch (Part B)

From Symmetric Encryption to Asymmetric Encryption

From Symmetric Encryption to Asymmetric Encryption

A crypto Hash algorithm in Python

A crypto Hash algorithm in Python

PyTorch model for Celsius to Fahrenheit Conversion

PyTorch model for Celsius to Fahrenheit Conversion

Loading Images to PyTorch tensors and normalization (Part B)

Loading Images to PyTorch tensors and normalization (Part B)

Loading Images to PyTorch tensors and normalization (Part A)

Loading Images to PyTorch tensors and normalization (Part A)

Loading CSV files to PyTorch with Numpy

Loading CSV files to PyTorch with Numpy

A Hashing Algorithm with the Python XOR operation for Cryptography (part A)

A Hashing Algorithm with the Python XOR operation for Cryptography (part A)

Python XOR operation for Cryptography

Python XOR operation for Cryptography

Loading images into PyTorch tensors

Loading images into PyTorch tensors

Loading CSV files into PyTorch tensors

Loading CSV files into PyTorch tensors

Substitution based Encryption and Decryption in Python (Part A)

Substitution based Encryption and Decryption in Python (Part A)

Substitution based Encryption and Decryption in Python (Part B)

Substitution based Encryption and Decryption in Python (Part B)

Crypto integrity and hashing files

Crypto integrity and hashing files

Symmetric encryption and padding

Symmetric encryption and padding

Symmetric encryption and corrupting one bit of the encrypted file

Symmetric encryption and corrupting one bit of the encrypted file

A Celsius to Fahrenheit model in PyTorch

A Celsius to Fahrenheit model in PyTorch

PyTorch tensor basics

PyTorch tensor basics

Machine Learning word problem: spam detection

Machine Learning word problem: spam detection

Machine Learning word problem: cancer detection from 3D scans

Machine Learning word problem: cancer detection from 3D scans

Formalizing Integrity for Cryptography

Formalizing Integrity for Cryptography

Formal definition of a cryptographic cipher and what makes it a secure cipher

Formal definition of a cryptographic cipher and what makes it a secure cipher

XOR in cryptography and an exercise (part 2)

XOR in cryptography and an exercise (part 2)

XOR in cryptography and an exercise (part 1)

XOR in cryptography and an exercise (part 1)

Tensor basics with PyTorch

Tensor basics with PyTorch

Training a Celsius to Fahrenheit ML model with PyTorch (Part 1)

Training a Celsius to Fahrenheit ML model with PyTorch (Part 1)

Machine Learning word problem: a model for language translation

Machine Learning word problem: a model for language translation

Machine Learning word problem: Modelling a steel blast furnace

Machine Learning word problem: Modelling a steel blast furnace

Machine Learning word problem: A super simple classifier to recommend movies on Netflix

Machine Learning word problem: A super simple classifier to recommend movies on Netflix

Machine Learning word problem: A classifier to detect objects in Facebook images

Machine Learning word problem: A classifier to detect objects in Facebook images

Anaconda and Jupyter Notebook basics for machine learning

Anaconda and Jupyter Notebook basics for machine learning

Main ideas for pre-training the BERT transformer

Main ideas for pre-training the BERT transformer