Machine Learning with Neural Networks

Description

Neural networks look like magic until you build a few. This course opens the box: you start with a single neuron, learn how a network actually learns, and finish by classifying plant photographs and reading the sentiment of product reviews, all with Keras and code that runs in Google Colab. The explanations are precise (there is real math, shown with a worked number) but never assume more than basic algebra.

What you will learn

• Neural network basics: layers, neurons and activation functions, how a network learns by gradient descent and backpropagation, your first network in Keras and how to read training curves.
• Training better networks: overfitting, dropout and early stopping, learning rate and batch size, and saving and loading models.
• Computer vision: how images are represented, convolutional networks, data augmentation, transfer learning with pretrained models and the common image pitfalls.
• Working with text: cleaning and tokenizing, bag of words and TF-IDF, sentiment analysis with classic models, word embeddings and transformers in a few lines of code.

How it is taught

Each lesson has an introduction from a real situation, a compact theory section with the definitions, equations and limitations, a diagram of the idea, a code demo with real outputs, exercises with hints and a summary. Because training curves and accuracy numbers are what you will look at at work, the lessons teach you to read them, not just produce them. Colab gives you a free GPU, so nothing has to be installed.

The project and files

The final module is a guided image project, Plant Image Classifier: you build a baseline CNN with augmentation, improve it with transfer learning, evaluate it, save the model and report the result. The course includes a dataset guide (classes, folder layout, source and license), a starter notebook with milestones, hints and a self-check list, and a worked solution that runs top to bottom on a Colab GPU in a few minutes. A product reviews dataset is provided for the text lessons.

What is included

Lessons that build from a single neuron to networks for images and text, a text dataset and an image dataset guide, a guided plant classifier project with a starter and a solution notebook, and a quiz for every module.

Who it is for

Deep learning is behind the most exciting AI you use every day, and this course lets you build it yourself, with free GPUs and no installation. You will understand what is inside a neural network instead of treating it as a black box, and finish with a working image classifier of your own. If you are ready for the next level, enroll now and start building.