sslides 0.0.19

Create awsome Solveit slides

sslides

Usage

Installation

Install latest from the GitHub repository:

$ pip install git+https://github.com/rleyvasal/sslides.git

or from pypi

$ pip install sslides

Documentation

Documentation can be found hosted on this GitHub repository’s pages. Additionally you can find package manager specific guidelines on pypi.

How to use

1. Import sslides functions from sslides import sshow ssave
2. Create a note with #| s to tell sslides all markdown below are your slides
3. The first note with # header becomes the title page
4. Create as many slides as you want with ## header - all content below that heading is the slide content
5. At the end of slides show or save (standalone html) sshow() or ssave()

from sslides import sshow

If you are new to using nbdev here are some useful pointers to get you started.

Introducing sslides

What is sslides

A tool for creating beautiful presentations from your solveit dialogs and research. - At the end of dialog create your slides - #| s marks the begining of slides - All Markdown and code cells below will be in slides - Code and code output hidden in dialog will be hidden in the slides - Navigate with arrow keys or hover on bottom right to see controls

Content Suported

• Markdown
• Bullet lists
• Latex Math
• Attachments from screenshots
• Code - highlighted by Pygments

Latex - Content too long, scroll option

Scaled Dot-Product Attention

The attention mechanism from “Attention is All You Need”:

$$\text{Attention}(Q, K, V) = \text{softmax}\left(\frac{QK^T}{\sqrt{d_k}}\right)V$$

Where $Q$ is queries, $K$ is keys, $V$ is values, and $d_k$ is the dimension of the keys.

Math Examples

Inline math: The quadratic formula is $x = \frac{-b \pm \sqrt{b^2-4ac}}{2a}$

Display math: $$\int_a^b f(x)dx = F(b) - F(a)$$

Statistics: $$\bar{x} = \frac{1}{n}\sum_{i=1}^n x_i$$

Calculus derivative: $$\frac{d}{dx}(x^n) = nx^{n-1}$$

Matrix: $$\begin{bmatrix} a & b \ c & d \end{bmatrix}$$

Attachments

Plots

Activation Functions Comparisons

• Code hidden in Solveit = Code hidden in slides

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-3, 3, 1000)

# Activation functions
relu = np.maximum(0, x)
gelu = 0.5 * x * (1 + np.tanh(np.sqrt(2/np.pi) * (x + 0.044715 * x**3)))
swish = x / (1 + np.exp(-x))
leaky_relu = np.where(x > 0, x, 0.01 * x)

fig, ax = plt.subplots(figsize=(10, 6))
ax.plot(x, relu, label='ReLU', linewidth=2)
ax.plot(x, gelu, label='GELU', linewidth=2)
ax.plot(x, swish, label='Swish', linewidth=2)
ax.plot(x, leaky_relu, label='Leaky ReLU', linewidth=2, linestyle='--')

ax.axhline(0, color='black', linewidth=0.5, alpha=0.3)
ax.axvline(0, color='black', linewidth=0.5, alpha=0.3)
ax.grid(True, alpha=0.3)
ax.legend(fontsize=12)
ax.set_xlabel('Input', fontsize=12)
ax.set_ylabel('Output', fontsize=12)
ax.set_title('Activation Functions Comparison', fontsize=14, pad=15)
plt.tight_layout()
plt.show()