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Are you bored with spending hours creating PowerPoint displays from prolonged texts? Do you want there was a quicker solution to convert your content material into partaking slides? Use ChatGPT to rework your textual content right into a presentation in simply minutes. Say goodbye to tedious copy-and-pasting and hey to an environment friendly and efficient resolution for all of your presentation wants!
To rework your textual content right into a PowerPoint presentation, you could run simply two steps:
- Let ChatGPT summarize your textual content
- Let ChatGPT write the Python code to transform the abstract into the PPTX format
Step one entails instructing ChatGPT to generate a presentation with a selected variety of slides based mostly on the given textual content. First, you could present ChatGPT with the textual content you wish to convert.
Use the next immediate to instruct ChatGPT to create the presentation:
Please convert the next textual content right into a ten-slide presentation: [enter the text]
ChatGPT will generate one thing much like the textual content proven within the following determine:
Picture by Writer
It’s essential to notice that the size and complexity of the textual content might impression the extent of element and coherence within the generated presentation. Due to this fact, preserving the unique textual content concise and arranged is advisable to acquire optimum outcomes.
Now that you’ve got obtained the generated presentation, it’s time to transform it into the extensively used PowerPoint format, .pptx. To perform this, we are going to ask ChatGPT to write down the Python code to generate it.
Use the next immediate to instruct ChatGPT to transform the presentation into pptx:
Please write the Python code to rework the earlier texts into the pptx format
ChatGPT will generate the Python code on your slides, equivalent to the next one:
from pptx import Presentation
# Create a presentation object
presentation = Presentation()
# Slide 1 - Title slide
slide1 = presentation.slides.add_slide(presentation.slide_layouts[0])
title = slide1.shapes.title
title.textual content = "Enhancing the Efficiency of a Machine Studying Algorithm"
# Slide 2 - Introduction
slide2 = presentation.slides.add_slide(presentation.slide_layouts[1])
content2 = slide2.shapes.title
content2.textual content = "Introduction"
# Slide 3 - Balancing Methods
slide3 = presentation.slides.add_slide(presentation.slide_layouts[1])
content3 = slide3.shapes.title
content3.textual content = "Balancing Methods"
# Slide 4 - Utilizing imbalanced-learn library
slide4 = presentation.slides.add_slide(presentation.slide_layouts[1])
content4 = slide4.shapes.title
content4.textual content = "Utilizing imbalanced-learn Library"
# Slide 5 - Information Import
slide5 = presentation.slides.add_slide(presentation.slide_layouts[1])
content5 = slide5.shapes.title
content5.textual content = "Information Import"
# Slide 6 - Mannequin Constructing
slide6 = presentation.slides.add_slide(presentation.slide_layouts[1])
content6 = slide6.shapes.title
content6.textual content = "Mannequin Constructing"
# Slide 7 - Imbalanced Dataset
slide7 = presentation.slides.add_slide(presentation.slide_layouts[1])
content7 = slide7.shapes.title
content7.textual content = "Imbalanced Dataset"
# Set the content material for every slide
slides = [slide2, slide3, slide4, slide5, slide6, slide7]
content material = [
"This tutorial belongs to the series How to improve the performance of a Machine Learning Algorithm.",
"A balanced dataset is a dataset where each output class is represented by the same number of input samples.",
"Balancing techniques include oversampling, undersampling, class weight, and threshold.",
"The imbalanced-learn library, part of the contrib packages of scikit-learn, is used in this tutorial.",
"Data is imported using the pandas library, and the target class is created based on cuisine.",
"The model is built using the Decision Tree algorithm, and evaluation metrics are calculated.",
"The classification report and various plots are generated for the imbalanced dataset."
]
# Add content material to every slide
for slide, content_text in zip(slides, content material):
content_placeholder = slide.placeholders[1]
content_placeholder.textual content = content_text
# Save the presentation
presentation.save("machine_learning_presentation.pptx")
As well as, ChatGPT recommends you put in the python-pptx library:
As soon as the library is put in, you’ll be able to run the generated code to provide your PowerPoint presentation.
Watch the next video to see ChatGPT in motion!
Congratulations! You’ve simply discovered how you can convert textual content to a PowerPoint presentation utilizing ChatGPT!
Because of the unbelievable capabilities of ChatGPT, changing textual content right into a PowerPoint presentation has change into a breeze. Following the two-step course of outlined on this weblog publish, you’ll be able to rapidly remodel prolonged texts into concise displays.
Bear in mind to supply clear and arranged textual content to acquire one of the best outcomes. With ChatGPT and some traces of Python code, you’ll be able to captivate your viewers with beautiful displays!
Angelica Lo Duca (Medium) (@alod83)is a researcher on the Institute of Informatics and Telematics of the Nationwide Analysis Council (IIT-CNR) in Pisa, Italy. She is a professor of “Information Journalism” for the Grasp diploma course in Digital Humanities on the College of Pisa. Her analysis pursuits embody Information Science, Information Evaluation, Textual content Evaluation, Open Information, Internet Purposes, Information Engineering, and Information Journalism, utilized to society, tourism, and cultural heritage. She is the creator of the ebook Comet for Information Science, revealed by Packt Ltd., of the upcoming ebook Information Storytelling in Python Altair and Generative AI, revealed by Manning, and co-author of the upcoming ebook Studying and Working Presto, by O’Reilly Media. Angelica can also be an enthusiastic tech author.
Authentic. Reposted with permission.