The Tutorials in this series are created in Python 3.5.2 on Ubuntu 16.04. Web application frameworks have become ubiquitous in developing a web application. They aid in developing dynamic web applications. Flask is a simple, powerful, and easy-to-learn Python micro framework. It is also one of the most widely used open source web application frameworks. In this series the learners will learn about the fundamental concepts of web development with hands-on experience to build a web app with Flask. Flask is light-weight and easy to extend. Therefore it is possible to extend the functionalities of the web app by integrating it with third-party APIs. Flask uses Jinja2 templating engine. We will cover models, views, controllers, web templates, forms, validation and integration with different third party packages etc. On completion of this course the learner will be fully equipped to build her own web application using the Flask micro framework. Read more
Foss : Python Flask - English
Outline: Python Virtual Environment Install pip3 Install virtualenv Create a Virtual Environment Activate the Virtual Environment Install Flask Write a Hello World Flask app Start th..
Outline: First Flask web app Importing flask module Python Decorators Web Server Gateway Interface Routes in Flask Static Routes View Functions Dynamic Routes 404 HTTP code Running..
Outline: Request response cycle in Flask Method attribute of the request object Sending data from client to server Query Arguments Form attribute of request object GET and POST method..
Outline: - Use of templates in Flask - Use of variables inside templates - Introduction to MVC Architecture - Model, View, Controller - render_template() method - Dynamic pages - Pas..
Foss : Python for Automation - English
Outline: About Python for Automation About Libraries required for Automation Glimpse of Basic level Spoken Tutorials available on Python for Automation series Glimpse of Intermediate lev..
Outline: Introduction to Automation Download package.txt file which contains library names used for automation series Create a Python virtual environment in Ubuntu Install all libraries ..
Outline: File Management using python automation. Libraries used for file management in python. Obtain the list of files. Separate the filename and its extension. List the unique extens..
Outline: Import necessary modules: Include os, shutil, tarfile, and datetime Implement compression logic for zip, tar.gz, and tar.bz2 formats Set up the overall backup process Ensure the..
Outline: About Encryption and Decryption About symmetric Encryption Import the necessary libraries for file operations and encryption Read file data and encrypt it using a provided key ..
Outline: About file conversion such as PDF to audio, JPG to PNG images, PDF to Docx using Python. About PyPDF2, pdfplumber, pyttsx3, pdf2docx, docx2pdf and PIL/Pillow libraries. Steps to ..
Outline: About Web scraping About the libraries used for web scraping process Scrape data from spoken tutorial website Python program to implement the web scrapping process Import the n..
Outline: About Spelling and Grammar Checker Python libraries used to implement the spelling and grammar checker Java and tkinter installation commands Import necessary modules and downlo..
Outline: About chatBot Building and training a chatbot Libraries required for building a chatbot Create an auto-updatable Q n A database for a chatbot Compare input questions to databas..
Outline: About log monitor Types of Logs Libraries used to log monitor Analyze log file About Syslog files Python program to Monitor logs continuously Produce log summary Plot the l..
Foss : Python for Machine Learning - English
Outline: Installation of Miniconda in Ubuntu OS Creating a conda environment for Machine Learning Activating conda environment for Machine Learning Download MLpackage.txt file Install a..
Outline: Introduction to Nearest Neighbors and K Nearest Neighbor Introduction to KNN classification Explanation about Iris dataset KNN working example using one of the iris feature Imp..
Outline: Introduction to K Nearest Neighbor Regression Various distance metrics used in KNN Importing the necessary libraries Loading the iris dataset Standard scaling of the dataset ..
Outline: About Linear Regression About Simple Linear Regression About Multiple Linear Regression About Evaluation Metrics Splitting the data into training and testing sets Implementing..
Outline: Introduction to Logistic Regression Introduction to Binary classification Introduction to Multi class classification About Purchase prediction Implementing Binary classificatio..
Outline: Implementing Multiclass classification Model Instantiation of Multiclass Classification and Model training Visualize this correlation using a heatmap Split the data into trainin..