How to Deploy LLM Applications Using Docker: A Step-by-Step Guide

This tutorial teaches you how to use Docker to build and deploy a document Q&A application on the Hugging Face Cloud.

Local AI with Docker, n8n, Qdrant, and Ollama

Learn how to build secure, local AI applications that protect your sensitive data using a low/no-code automation framework.

Unsloth Guide: Optimize and Speed Up LLM Fine-Tuning

Fine-tuning the Llama 3.1 model to solve specialized algebra problems with high accuracy and detailed results using Unsloth.

Streamlining MLOps Workflows

A lightweight, daemonless Docker Desktop alternative that streamlines container management, enabling fast training, evaluation, and deployment of machine learning models.

Fine-Tuning Phi-3.5 on E-Commerce Classification Dataset

Discover Microsoft's new LLM series and boost your model's accuracy from 65% to 86% by fine-tuning it on the E-commerce classification dataset.

Fine-tuning GPT-4o Mini: A Step-by-Step Guide

Customize the GPT-4o Mini model to classify posts from Reddit into "stressful" and "non-stressful" labels.

Jenkins for MLOps: A Complete CI/CD Tutorial

Learn how to install Jenkins on Windows, set up and run Jenkins agents and pipelines, and build MLOps projects with Jenkins pipelines from model training to model serving.

spaCy Resume Analysis

In this project, we will use Spacy for entity recognition on 200 resumes and experiment with various NLP tools for text analysis. The main purpose is to help recruiters quickly go through hundreds of applications. We have also added a skills-matching feature.

Analyzing and Predicting Consumer Engagement

In this project, we will use the Internet News and Consumer Engagement dataset from Kaggle to predict top article and popularity score. We will explore the data to discover patterns, such as correlation, distribution, mean, time series analysis, text regression, and text classifier.

Vaccine Update Dashboard

In this project, I used Pandas for web scraping data from pharmaceutical-technology.com. Then, I created a Sqlite3 database with three tables to store the data. It took several attempts to get everything working smoothly. The notebook is fully automated with interactive plots.

Yoga Pose Classification with DagsHub Streaming

In this project, we will fine-tune the ResNet34 model to classify Yoga Poses using DagsHub streaming.

Urdu Automatic Speech Recognition State of the Art Solution

In this project, we will fine-tune the Facebook/wav2vec2-Xls-r-300m model on the Urdu subset of the common_voice dataset licensed under CC-0. This model architecture has enabled data scientists to develop state-of-the-art speech-to-text applications in over 80 languages.

ChatGPT For Data Science Projects

In this tutorial, we will learn how to use ChatGPT for an end-to-end data science project. We will create a project outline, write Python code, conduct research, and debug the application using various prompts. Additionally, we will explore tips for writing effective prompts.

Getting Started with SHAP Values

This tutorial covers SHAP values and how to interpret machine learning results with the SHAP Python package.

LlamaIndex: Adding Personal Data to LLMs

LlamaIndex is your friendly data sidekick for building LLM-based apps. You can easily ingest, manage, and retrieve both private and domain-specific data using natural language.

Time Series Analysis: ARIMA Models in Python

ARIMA models are a popular tool for time series forecasting and can be implemented in Python using the `statsmodels` library.

A Complete Guide to Data Augmentation

Learn about data augmentation techniques, applications, and tools with a TensorFlow and Keras tutorial.

Fine-Tuning LLaMA 2: A Step-by-Step Guide to Customizing the Large Language Model

Fine-Tuning LLaMA 2: A Step-by-Step Guide to Customizing the Large Language Model

Mistral 7B Tutorial

The tutorial covers accessing, quantizing, fine-tuning, merging, and saving this powerful 7.3 billion parameter open-source language model.

Fine-tuning Stable Diffusion XL with DreamBooth and LoRA

In this tutorial, we will learn about Stable Diffusion XL and Dream Booth, and how to access the image generation model using the diffuser library. Additionally, we will learn to fine-tune the model on personal photos and evaluate its performance. If you're a newcomer to AI, we suggest taking an AI

StableDiffusion Web UI: A Comprehensive User Guide for Beginners

Learn how to install and use Stable Diffusion Web UI easily to generate high-quality images on your laptop.

Comprehensive Guide to Zephyr-7B: Features, Usage, and Fine-tuning

Learn everything about Zephyr-7B, including its training, how to access it, and how to fine-tune it on a custom database using free Kaggle GPUs.

OpenAI Function Calling Tutorial

Learn how OpenAI's new Function Calling capability enables GPT models to generate structured JSON output, resolving common dev issues caused by irregular outputs.

AutoML Discovery and Approach - ML 070

AutoML (automated machine learning) has become a hot topic over the past few years. Abid Ali Awan joins the show to share his approach to AutoML, when and how to utilize it compared to classic approaches. Ben and Abid also discuss open-source vs. proprietary platforms.

CI/CD For Machine Learning

In this project, we will be using scikit-learn pipelines to train our random forest algorithm and build a drug classifier. After training, we will automate the evaluation process using CML. Finally, we will build and deploy the web application to Hugging Face Hub.

Machine Learning Workflow with Scikit-learn Pipelines

Learn how to enhance the quality of your machine learning code using Scikit-learn Pipeline and ColumnTransformer.

GitHub Actions For Machine Learning Workflows

Learn how to automate machine learning training and evaluation using scikit-learn pipelines, GitHub Actions, and CML.

ML Workflow Orchestration With Prefect

Learn everything about a powerful and open-source workflow orchestration tool. Build, deploy, and execute your first machine learning workflow on your local machine and the cloud with this simple guide.

How to Run Llama 3 Locally: A Complete Guide

Run LLaMA 3 locally with GPT4ALL and Ollama, and integrate it into VSCode. Then, build a Q&A retrieval system using Langchain, Chroma DB, and Ollama.

Fine-Tuning Llama 3 and Using It Locally: A Step-by-Step Guide

We'll fine-tune Llama 3 on a dataset of patient-doctor conversations, creating a model tailored for medical dialogue. After merging, converting, and quantizing the model, it will be ready for private local use via the Jan application.

Fine-Tune and Run Inference on Google's Gemma Model Using TPUs for Enhanced Speed and Performance

Learn to infer and fine-tune LLMs with TPUs and implement model parallelism for distributed training on 8 TPU devices.

GitHub Actions and MakeFile: A Hands-on Introduction

Learn to automate the generation of data reports using Makefile and GitHub Actions.

Groq LPU Inference Engine

Learn about the Groq API and its features with code examples. Additionally, learn how to build context-aware AI applications using the Groq API and LlamaIndex.

DuckDB Tutorial: Building AI Projects

This tutorial guides you through DuckDB's key features and practical applications, including building tables, performing data analysis, building an RAG application, and using an SQL query engine with LLM.

Multiple-step AI Agent using the LangChain ecosystem and Cohere Command R+ model

This AI application will take the user's query to search the web using the Tavily API and generate the Python code. Then, it will use Python REPL to execute the code and return the visualization that the user requested.

Fine-Tuning Llama 3.1 for Mental Health Disorder Classification

Get started with the new Llama models and customize Llama-3.1-8B-It to predict various mental health disorders from the text.

Fine-Tuning Gemma 2 and Using it Locally

This is a simple guide to fine-tuning Gemma 2 9B-It on patient-doctor conversations and converting the model into GGUF format so that it can be used locally with the Jan application.

DeepChecks: Automating Machine Learning Testing

Learn how to perform data and model validation to ensure robust machine learning performance using our step-by-step guide to automating testing with DeepChecks.

Mastering Digital Art with Stable Diffusion

This ebook explains how to make Stable Diffusion work for you. You can provide a text prompt to create a picture or use another image as inspiration for your drawing idea. However, to create high-quality images effectively, you need to understand and adjust certain settings in Stable Diffusion.

LlaMA-Factory WebUI Beginner's Guide: Fine-Tuning LLMs

Learn how to fine-tune LLMs on custom datasets, evaluate performance, and seamlessly export and serve models using the LLaMA-Factory's low/no-code framework.

Time Series Forecasting With TimeGPT

Learn how to fine-tune TimeGPT, the first foundational model for time series datasets, for forecasting and anomaly detection with just a few lines of code.