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Track your journey through AI and Machine Learning fundamentals

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Basics

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Data Scaling

Understand how to normalize and standardize data for AI models.

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Linear Regression

Dive into linear regression concepts with interactive visualizations.

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Loss and Metric

Discover how loss functions and metrics are used to evaluate AI models.

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Gradient Descent

Visualize how gradient descent optimizes AI models.

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Stochastic Gradient Descent

Learn how SGD works and why it's important for training neural networks.

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Tensors

Get introduced to tensors, the building blocks of modern AI.

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Neural Network

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Perceptron

Learn the basics of perceptrons, the building blocks of neural networks.

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Backpropagation

Understand how neural networks learn through backpropagation.

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Multi-layer Neural Networks

Explore the architecture of multi-layer networks and their working.

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Deep Learning

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Introduction to Deep Learning

Learn the foundations of deep learning and its applications.

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Data for Training

Learn how to prepare datasets for training deep learning models.

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Activation Functions

Explore activation functions like ReLU, sigmoid, and tanh.

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Optimizers

Visualize optimization techniques like SGD, Adam, and more.

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Loss Functions

Understand how loss functions work to optimize models.

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Visual Demos

Understand deep learning concepts through interactive visual demos.

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Manage Model

Learn how to manage, train, and evaluate models in deep learning.

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Computer Vision

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Visual Demo

Explore visual AI tasks through demos and interactive tools.

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Image Data

Learn how to prepare image data for AI tasks.

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Images to Training Input

Understand how images are transformed for training neural networks.

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Convolution Kernels

Understand convolution kernels and their role in CNNs.

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Pooling

Learn about pooling operations for feature reduction in CNNs.

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Audio Processing

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Visual Demo

Explore audio-based AI tasks through interactive tools.

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Audio Basics

Learn the basics of audio data and processing techniques.

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Speech Sampling

Understand how speech is sampled and processed for AI models.

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Text Processing

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Spam Detection

Learn how AI detects spam using text data.

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Question and Answer

Understand how Q&A systems are built using AI.

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Word Embeddings

Explore word embeddings for natural language processing.

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Position Embeddings

Learn about position embeddings in transformer models.

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Attention Mechanisms

Explore how attention mechanisms work in NLP models.

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Attention Heatmap

Visualize attention mechanisms using heatmaps.

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BERT Explorer

Visualize how BERT processes text for various NLP tasks.

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