Web Scraping with Python Beautiful Soup and Requests
Exporting data extracted by Beautifulsoup into CSV, Excel files
Fundamental knowledge of Python 3
When the webpage structure is so complicated, making it difficult to extract specific pieces of data, or when you need to open so many pages to extract data from each of them, the manual process can become boring and time-wasting, and that is when automated Web Scraping can make the process more efficient and effective.
Web scraping is the practice of gathering data from internet automatically by computer program without using API and web browser.
Instead of copy pasting important data by a human from a web browser visiting a website, web scraping can automate the process. Web scraping is now very important for a data scientist. A data scientist analysis data collected from various media. Now most of the data comes from different websites. As Python programming is very popular for harvesting data, many data scientist use Python programming to solve that.
I created this course as short and useful as possible. Within short period of time, you can learn all the important topics and techniques about web scraping using Python. So using the same technique you can apply to scrap other similar webpage as well using Python.
This Web Scraping course covers the following topics:
Learn Python Web Scraping fundamentals.
Use BeautifulSoup & Requests to scrape websites with Python
Learn how to save your scraped output into dataframe
So let’s start your Web Scraping real-life project.
Who this course is for:
Curious in Web Scraping
Curious in Python BeautifulSoup Library
Anyone who wants to automate the task of copying contents from websites
Use expo to test the React Native mobile application
Are you ready to take your programming skills to the next level? If you’re looking to learn how to create a react native chatbot mobile app that uses the API from OpenAI for interactions, then the Getting Started with ChatGPT API Udemy Course is perfect for you! In this course, you’ll learn everything you need to know about building a chatbot app using ChatGPT API, from setting up your development environment to creating interactive features. Let’s take a closer look at what you can expect from this course.
Section 1: Discover the Power of ChatGPT API
If you’re new to ChatGPT API, you may be wondering what makes it so powerful. This section of the course will introduce you to the world of ChatGPT API and show you how it can be used to create amazing chatbots. You’ll learn about the features and capabilities of ChatGPT API and see real-world examples of how it’s being used to power chatbot applications.
Section 2: Building a React Native Chatbot App
Now that you understand the basics of ChatGPT API, it’s time to start building your own chatbot app. This section of the course will walk you through the process of creating a React Native chatbot app that uses ChatGPT API for interactions. You’ll learn how to set up your development environment, create a user interface, and integrate ChatGPT API into your app. By the end of this section, you’ll have a fully functional chatbot app that you can use to interact with users.
How to implement a Artificial Deep Neural Network from scratch
How back-propagation algorithm works
Convolutional Neural Network Architectures
How to build a handwritten digit recogniser model
No Deep Learning experience needed. You will learn everything you need to know
It is structured to help you genuinely learn Deep Learning by starting from the basics until advanced concepts. We will learn and code every component of a Deep learning architecture from scratch, uncovering all the magic behind Artificial Neural Networks.
To prepare the students for real life, we will develop our ANN framework following the TensorFlow API, and we will compare our implementation with Tensorflow.js, this way you will know what is under the hood of the Deep learning libraries.
In this course, we will create a handwritten digit recognizer model using three different model approaches:
Fully Connected Neural Network (also known as a DenseNet) Using TensorFlow.js
Convolutional Neural Network(also known as a ConvNet or CNN) Using TensorFlow.js
Deep learning is a field of study traditionally reserved for researchers or engineers with advanced degrees, and because of that, many developers feel very intimidated to learn this technology. However, when you start learning the mystery behind the “magic”, you will realize that there is no reason to be intimidated. And that’s why I decided to create this course.
By following this course until the end, you will get insights and feel empowered to dive deep into the Deep Learning field to improve the experience of your projects.