Scratch

“It’s cool work,” says Matthew Gudzial, an AI researcher on the University of Alberta, who developed a similar game generator just a few years ago.  Genie was trained on 30,000 hours of...

Gain a deeper understanding of Gaussian processes by implementing them with only NumPy.Gaussian Processes (GPs) are an incredible class of models. There are only a few Machine Learning algorithms that offer you an accurate...

From Text to Tokens: Your Step-by-Step Guide to BERT TokenizationBy the point you finish reading this text, you’ll not only understand the ins and outs of the BERT tokenizer, but you’ll even be equipped...

An introduction to Q-Learning with a practical Python exampleThe agent is the one selecting the course of actions. In the instance, the agent is the player who controls the joystick deciding the following move...

// Importing required librariesimport numpy as np// Preparing datasetx = np.array(,,])y = np.array(,,])// Defining the activation function# Activation function # Here we have now used sigmoid function that provides the output between 0 and...

Constructing a Transformer model step-by-step in PytorchMerging all of it together:class Transformer(nn.Module):def __init__(self, src_vocab_size, tgt_vocab_size, d_model, num_heads, num_layers, d_ff, max_seq_length, dropout):super(Transformer, self).__init__()self.encoder_embedding = nn.Embedding(src_vocab_size, d_model)self.decoder_embedding = nn.Embedding(tgt_vocab_size, d_model)self.positional_encoding = PositionalEncoding(d_model, max_seq_length)self.encoder_layers = nn.ModuleList()self.decoder_layers =...

I like to recommend fooling around with different values of the parameters (i.e., perplexity, learning rate, early exaggeration, etc.) to see how the answer differs (See the original paper and the scikit-learn documentation for...

In this text, I'll take you thru the implementation of Batch Gradient Descent, Stochastic Gradient Descent, and Mini-Batch Gradient Descent coding from scratch in python. This can be beginners friendly. Understanding gradient descent method...