Master Modern AI Engineering with Production Code

Building a Language Model Application with LangChain: A Beginners Guide

LLM Workflows

With Generative AI sweeping the world, learning to build and develop applications with large language models (LLMs) is crucial. LLMs are machine learning models that can understand and generate human-like language text.

Building a Neural Network Model Using TensorFlow

Generative AI Foundations

Traditional machine-learning algorithms like Random Forest and XGBoost are very effective in building applications using structured tabular data. However, they fall short when dealing with complex tasks like image recogn...

Building a Neural Network using PyTorch

Developer Tools

Have you ever wondered how neural networks learn to make predictions or classify data? Neural networks serve as the foundation of artificial intelligence, allowing machines to recognize patterns and make informed decisio...

Decision Trees for Classification and Regression

Machine learning

Decision trees are a common type of machine learning model used for binary classification tasks. The natural structure of a binary tree lends itself well to predicting a “yes” or “no” target. It is traversed sequentially...

Depth-First Search: Conceptual

Web development

Depth-First Search is an algorithm used for searching tree data structures for a particular node, or node with a particular value associated with it. Depth-First Search is also more generally used as a tree traversal alg...

EDA Prior To Fitting a Regression Model

Data visualization

Before fitting any model, it is often important to conduct an exploratory data analysis (EDA) in order to check assumptions, inspect the data for anomalies (such as missing, duplicated, or mis-coded data), and inform fea...

Feature Importance

Machine learning

When we fit a supervised machine learning (ML) model, we often want to understand which features are most associated with our outcome of interest. Features that are highly associated with the outcome are considered more...

Google VaultGemma: A Guide to Privacy-First LLMs

LLM Workflows

AI models are evolving across industries as powerful tools, but the question about how to keep private data safe still hangs over its use. Traditional large language models memorize and reveal parts of their training dat...

History of Chatbots

Machine learning

In October of 1950, Alan Turing proposed an approach for evaluating a computer’s intelligence and famously named his method, The Imitation Game. The premise is that an interrogator talks to two people through a “typewrit...

How to Fine Tune Large Language Models (LLMs)

LLM Workflows

LLM fine-tuning is the process of taking a pre-trained LLM and training it on a specific dataset to improve its performance for a particular use case. This approach is cost-effective, as it adapts an existing model to a ...

How to Run Llama 3 Locally

LLM Workflows

Llama 3 is a powerful large language model (LLM) that has been gaining popularity among developers for its ability to generate human-like text. With fine-tuning options, context understanding, and improved performance, L...

How to Use Hugging Face: Beginner's Guide to AI Models

Cloud & Full-Stack AI

Hugging Face is a leading open-source platform for building and deploying machine learning (ML) models, especially in natural language processing (NLP). It provides powerful tools like the Transformers library, a Model H...

How to set up a deep learning environment

Machine learning

TensorFlow(TF), developed by Google Brain, is the most well-known library used in production fordeep learningmodels and it has a very large community. However, TensorFlow has a steep learning curve. On the other hand,Ker...

Introducing Jupyter Notebook

Developer tools

Jupyter Notebook (sometimes called IPython Notebook) is a popular way to write and run Python code, especially for data analysis, data science and machine learning. Jupyter Notebooks are easy-to-use because they let you...

Introduction to Regression Analysis

Machine learning

We often hear of new, complex “machine learning” methods that allow us to generate human language, very accurately predict changes in the stock market, or recognize that an image contains a person or specific object. Whi...

Log Transformation in Linear Regression: When and How to Use It

Data visualization

When analyzing data using linear regression, we often assume a linear relationship between the independent and dependent variables. However, real-world data doesn’t always behave that way. In many cases, the dependent va...

Normalization: Min-Max and Z-Score Normalization

Machine learning

Normalizationis a useful data preprocessing technique used to adjust the scale of numeric data features so that they fall within a particular range or follow a specific distribution. This is especially important when dat...

Principal Component Analysis

Data visualization

Principal Component Analysis (PCA)is adimension reductionmethod that is frequently used in exploratory data analysis and machine learning. This means that PCA can be leveraged to reduce the number of variables (dimension...

Prompt Engineering vs Fine Tuning: When to Use Each

LLM Workflows

When building AI applications using large language models(LLMs), developers face a crucial decision in the fine-tuning vs prompt engineering debate. Choose LLM fine-tuning when you need specialized domain knowledge, have...

Scikit-Learn Cheatsheet

Machine learning

Scikit-learnis a library in Python that provides many unsupervised andsupervised learningalgorithms. It’s built upon some of the technology you might already be familiar with, likeNumPy, pandas, and Matplotlib!

Scikit-Learn Tutorial: Python Machine Learning Model Building

Developer tools

Scikit-learn(often shortened to “sklearn”) is a free, open-source machine learning library for Python that provides simple and efficient tools for data analysis and modeling. Built onNumPy,SciPy, andmatplotlib,scikit-lea...

The Machine Learning Process: Look What Taylor Swift Made Me Do

Machine learning

For the past few months, the Curriculum team at Codecademy has been hard at work creating Machine Learning courses. While we all loved writing courses, we also wanted to see what we could do with real-world data. As a re...

Transformer Architecture Explained With Self-Attention Mechanism

Generative AI Foundations

Transformers are deep learning models that help the large language models (LLMs) understand the contextual meaning of text inputs and generate relevant text outputs. In this article, we'll discuss how the transformer arc...

Understanding Convolutional Neural Network (CNN) Architecture

Generative AI Foundations

We use artificial neural networks to build deep learning applications for tasks like image recognition, text classification, and speech recognition. For image classification with fewer variations in training data and a s...

What is One Hot Encoding and How to Implement it in Python?

Machine learning

When working with real-world datasets, attributes like gender, color, names of places, and product type contain vital information that can help build efficientmachine learning (ML)models. As ML models understand only num...

Common Applications of Deep Learning

Data visualization

So far, we have gone from single-layerneural networksto multi-layer models with many hidden layers. We have also reviewed how these neural networks can serve as powerful tools for both classification and regression tasks...

Dangers of the Black Box

Data visualization

When talking about machine learning,deep learning, and artificial intelligence, people tend to focus on the progress and amazing feats we could potentially achieve. While it is true that these disciplines have the potent...

Deep Learning Workflow

Machine learning

Successfully usingdeep learningrequires more than just knowing how to buildneural networks; we also need to know the steps required to apply them in real-world settings effectively.

Ethics of Chatbots

Machine learning

Imagine you are shopping online and come across a live chat feature on a website. You decide to begin a chat to get some advice on finding the right product to purchase. The representative on the other end appears to be...

Long Short Term Memory Networks

Machine learning

Information Persistence andNeural Networks

Netflix Recommendation Engine

Machine learning

You may have heard the term “big data“ thrown around, but do you understand what it is? Big data refers to massive datasets that can be used to reveal patterns and trends. Any large quantity of information, from sports s...

Regression vs. Classification

Machine learning

Machine Learning is a set of many different techniques that are each suited to answering different types of questions.

Supervised vs. Unsupervised Learning: what's the difference?

Machine learning

As humans, we have many different ways we learn things. The way you learned calculus, for example, is probably not the same way you learned to stack blocks. The way you learned the alphabet is probably wildly different f...

The Machine Learning Process

Data visualization

When people think of Machine Learning, they often think of a program that is taking in data and spitting out predictions and insights. The process of performing Machine Learning often requires many more steps before and...

The Machine Learning Process: Identifying Storylines in Survivor

Machine learning

For the past few months, the Curriculum team at Codecademy has been hard at work creating Machine Learning courses. While we all loved writing courses, we also wanted to see what we could do with real-world data. As a re...

Training Set vs Validation Set vs Test Set

Machine learning

Inmachine learning, data is everything. However, just having data isn’t enough — how we divide it can make or break our model’s performance. This is where the concepts of training set, validation set, and test set come i...

Understanding Neural Networks and Their Components

Generative AI Foundations

In the age of deep learning and generative AI, neural network models are at the forefront of innovation. We use neural networks to build deep learning applications for tasks like image recognition, text classification, a...

Understanding Overfitting in Machine Learning

Machine learning

Often in Machine Learning, we feed a huge amount of data to an algorithm that then learns how to classify that input based on rules it creates. The data we feed into this algorithm, thetraining data, is hugely important....

What Is Deep Learning?

Data visualization

Have you ever wondered what powers ChatGPT? What technology developers are using to create self-driving cars? How your phone can recognize faces? Why it seems like your photos app is better at recognizing your friends’ f...

What are Chatbots

Machine learning

From the customer support dialog boxes you find on e-commerce websites to virtual assistants like Siri and Alexa, it’s likely that you’ve encountered chatbots frequently in your everyday life. Like its name suggests, a c...

What are Neural Networks?

Machine learning

As you are reading this article, the very same brain that sometimes forgets why you walked into a room is magically translating these pixels into letters, words, and sentences — a feat that puts the world’s fastest super...

What is Reinforcement Learning? With Examples

AI Agents & Automation

Reinforcement learning (RL) is a machine learning approach where an AI agent learns to make optimal decisions through trial and error, receiving rewards for good actions and penalties for bad ones. Imagine teaching a dog...