This document introduces a Python programming course taught by Ghulam Mustafa Shoro at the University of Sindh. The course covers Python programming theory and lab work. It meets once a week for theory and once a week for lab. The textbook used is "Python for Everybody". The course aims to teach basic Python programming and covers chapters 1-5 of the textbook. Upon completing the course, students will be prepared for more advanced Python courses.
This document provides an introduction and overview of the Python programming language. It covers Python's history and key features such as being object-oriented, dynamically typed, batteries included, and focusing on readability. It also discusses Python's syntax, types, operators, control flow, functions, classes, imports, error handling, documentation tools, and popular frameworks/IDEs. The document is intended to give readers a high-level understanding of Python.
The document provides an introduction and overview of the Python programming language. It discusses that Python is an interpreted, object-oriented, high-level programming language that is easy to learn and read. It also covers Python features such as portability, extensive standard libraries, and support for functional, structured, and object-oriented programming. The document then discusses Python data types including numbers, strings, and various Python syntax elements before concluding with the history and evolution of the Python language through various versions.
** Python Certification Training: https://www.edureka.co/python **
This Edureka tutorial on "Python Tutorial for Beginners" (Python Blog Series: https://goo.gl/nKQJHQ) covers all the basics of Python. It includes python programming examples, so try it yourself and mention in the comments section if you have any doubts. Following are the topics included in this PPT:
Introduction to Python
Reasons to choose Python
Installing and running Python
Development Environments
Basics of Python Programming
Starting with code
Python Operators
Python Lists
Python Tuples
Python Sets
Python Dictionaries
Conditional Statements
Looping in Python
Python Functions
Python Arrays
Classes and Objects (OOP)
Conclusion
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This document discusses data visualization tools in Python. It introduces Matplotlib as the first and still standard Python visualization tool. It also covers Seaborn which builds on Matplotlib, Bokeh for interactive visualizations, HoloViews as a higher-level wrapper for Bokeh, and Datashader for big data visualization. Additional tools discussed include Folium for maps, and yt for volumetric data visualization. The document concludes that Python is well-suited for data science and visualization with many options available.
The amount of data available to us is growing rapidly, but what is required to make useful conclusions out of it?
Outline
1. Different tactics to gather your data
2. Cleansing, scrubbing, correcting your data
3. Running analysis for your data
4. Bring your data to live with visualizations
5. Publishing your data for rest of us as linked open data
Python is a popular programming language introduced in 1991 by Guido van Rossum. It can be used for web development, software development, mathematics, and system scripting. The document discusses basics of Python including flow charts, algorithms, installing Python IDLE, and using variables in Python to store data values.
This document introduces a Python programming course taught by Ghulam Mustafa Shoro at the University of Sindh. The course covers Python programming theory and lab work. It meets once a week for theory and once a week for lab. The textbook used is "Python for Everybody". The course aims to teach basic Python programming and covers chapters 1-5 of the textbook. Upon completing the course, students will be prepared for more advanced Python courses.
This document provides an introduction and overview of the Python programming language. It covers Python's history and key features such as being object-oriented, dynamically typed, batteries included, and focusing on readability. It also discusses Python's syntax, types, operators, control flow, functions, classes, imports, error handling, documentation tools, and popular frameworks/IDEs. The document is intended to give readers a high-level understanding of Python.
The document provides an introduction and overview of the Python programming language. It discusses that Python is an interpreted, object-oriented, high-level programming language that is easy to learn and read. It also covers Python features such as portability, extensive standard libraries, and support for functional, structured, and object-oriented programming. The document then discusses Python data types including numbers, strings, and various Python syntax elements before concluding with the history and evolution of the Python language through various versions.
** Python Certification Training: https://www.edureka.co/python **
This Edureka tutorial on "Python Tutorial for Beginners" (Python Blog Series: https://goo.gl/nKQJHQ) covers all the basics of Python. It includes python programming examples, so try it yourself and mention in the comments section if you have any doubts. Following are the topics included in this PPT:
Introduction to Python
Reasons to choose Python
Installing and running Python
Development Environments
Basics of Python Programming
Starting with code
Python Operators
Python Lists
Python Tuples
Python Sets
Python Dictionaries
Conditional Statements
Looping in Python
Python Functions
Python Arrays
Classes and Objects (OOP)
Conclusion
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
This document discusses data visualization tools in Python. It introduces Matplotlib as the first and still standard Python visualization tool. It also covers Seaborn which builds on Matplotlib, Bokeh for interactive visualizations, HoloViews as a higher-level wrapper for Bokeh, and Datashader for big data visualization. Additional tools discussed include Folium for maps, and yt for volumetric data visualization. The document concludes that Python is well-suited for data science and visualization with many options available.
The amount of data available to us is growing rapidly, but what is required to make useful conclusions out of it?
Outline
1. Different tactics to gather your data
2. Cleansing, scrubbing, correcting your data
3. Running analysis for your data
4. Bring your data to live with visualizations
5. Publishing your data for rest of us as linked open data
Python is a popular programming language introduced in 1991 by Guido van Rossum. It can be used for web development, software development, mathematics, and system scripting. The document discusses basics of Python including flow charts, algorithms, installing Python IDLE, and using variables in Python to store data values.
Python is a versatile, object-oriented programming language that can be used for web development, data analysis, and more. It has a simple syntax and is easy to read and learn. Key features include being interpreted, dynamically typed, supporting functional and object-oriented programming. Common data types include numbers, strings, lists, dictionaries, tuples, and files. Functions and classes can be defined to organize and reuse code. Regular expressions provide powerful string manipulation. Python has a large standard library and is used widely in areas like GUIs, web scripting, AI, and scientific computing.
This document provides an overview of the Python programming language. It discusses Python's history and evolution, its key features like being object-oriented, open source, portable, having dynamic typing and built-in types/tools. It also covers Python's use for numeric processing with libraries like NumPy and SciPy. The document explains how to use Python interactively from the command line and as scripts. It describes Python's basic data types like integers, floats, strings, lists, tuples and dictionaries as well as common operations on these types.
This presentation provides the information on python including the topics Python features, applications, variables and operators in python, control statements, numbers, strings, print formatting, list and list comprehension, dictionaries, tuples, files, sets, boolean, mehtods and functions, lambda expressions and a sample project using Python.
This document provides an overview of data visualization in Python. It discusses popular Python libraries and modules for visualization like Matplotlib, Seaborn, Pandas, NumPy, Plotly, and Bokeh. It also covers different types of visualization plots like bar charts, line graphs, pie charts, scatter plots, histograms and how to create them in Python using the mentioned libraries. The document is divided into sections on visualization libraries, version overview of updates to plots, and examples of various plot types created in Python.
This document provides an overview of Continuum Analytics and Python for data science. It discusses how Continuum created two organizations, Anaconda and NumFOCUS, to support open source Python data science software. It then describes Continuum's Anaconda distribution, which brings together 200+ open source packages like NumPy, SciPy, Pandas, Scikit-learn, and Jupyter that are used for data science workflows involving data loading, analysis, modeling, and visualization. The document outlines how Continuum helps accelerate adoption of data science through Anaconda and provides examples of industries using Python for data science.
This Edureka Python tutorial is a part of Python Course (Python Tutorial Blog: https://goo.gl/wd28Zr) and will help you in understanding what exactly is Python and its various applications. It also explains few Python code basics like data types, operators etc. Below are the topics covered in this tutorial:
1. Introduction to Python
2. Various Python Features
3. Python Applications
4. Python for Web Scraping
5. Python for Testing
6. Python for Web Development
7. Python for Data Analysis
This document provides an introduction to creating a simple calculator application using Python. It discusses that Python is a popular programming language used for web development, software development, mathematics, and system scripting. It then describes that the project will create a graphical user interface (GUI) calculator application using Python and the Tkinter library. Tkinter provides an object-oriented interface to create GUI applications in Python. The document outlines the system requirements, tools and technologies used, and includes a use case diagram for the calculator application.
This document provides an introduction to First Order Predicate Logic (FOPL). It defines FOPL as symbolized reasoning where sentences are broken down into subjects and predicates. FOPL is more expressive than propositional logic and allows representing almost any English sentence. It discusses features of FOPL such as generalization of propositional logic and more powerful representation. Applications of FOPL include presenting arguments, determining validity, and formulating theories. The document also defines key terms in FOPL such as constants, variables, functions, and predicates.
Python is an interpreted programming language created by Guido van Rossum in 1991. It has an elegant syntax, large standard library, and is used widely for data science, machine learning, web development, and more. Key Python libraries for data analysis include NumPy, pandas, and matplotlib. Pandas allows importing and cleaning data from files like CSVs, and matplotlib can be used to visualize and present analyzed data. For example, a program can use pandas to read baby name data from a CSV, find the most popular name with the highest birth count, and plot the results to clearly present the findings.
This document provides an overview of Pandas, a Python library used for data analysis and manipulation. Pandas allows users to manage, clean, analyze and model data. It organizes data in a form suitable for plotting or displaying tables. Key data structures in Pandas include Series for 1D data and DataFrame for 2D (tabular) data. DataFrames can be created from various inputs and Pandas includes input/output tools to read data from files into DataFrames.
Python An Introduction, A presentation Developed by Swarit Wadhe. This Slide Will Give you basic information about python (Origin, Codes and difference from other languages).
I hope you'll find this helpfull and if you do please share it with your fellows.
This Edureka Python Programming tutorial will help you learn python and understand the various basics of Python programming with examples in detail. Below are the topics covered in this tutorial:
1. Python Installation
2. Python Variables
3. Data types in Python
4. Operators in Python
5. Conditional Statements
6. Loops in Python
7. Functions in Python
8. Classes and Objects
Best Data Science Ppt using Python
Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data.
The document provides an introduction to Python programming. It discusses key concepts like variables, data types, operators, and sequential data types. Python is presented as an interpreted programming language that uses indentation to indicate blocks of code. Comments and documentation are included to explain the code. Various data types are covered, including numbers, strings, booleans, and lists. Operators for arithmetic, comparison, assignment and more are also summarized.
Installing Anaconda Distribution of PythonJatin Miglani
This document provides an overview of Anaconda, how it differs from a standard Python distribution, and how to install and use it. Anaconda is an open-source distribution of Python and R that includes over 1,000 data science packages to simplify package management. It uses the conda package manager to handle environments and installation of packages from various repositories. The document outlines how to install Anaconda, use conda commands to manage packages and environments, and integrate Anaconda with the PyCharm IDE.
The document provides an introduction to Python programming. It discusses installing and running Python, basic Python syntax like variables, data types, conditionals, and functions. It emphasizes that Python uses references rather than copying values, so assigning one variable to another causes both to refer to the same object.
5 Simple Steps To Install Python On Windows | Install Python 3.7 | Python Tra...Edureka!
** Python Certification Training: https://www.edureka.co/python **
This Edureka tutorial on Installing Python on Windows Tutorial covers all the aspects of installing and setting up Python to write code in. It is pretty simple and straightforward to setup Python completely in Windows as shown.
Following topics are covered in this PPT:
Agenda
Introduction to Python
Popularity of Python
Why should you learn Python?
Installing Python
Python Development Environments
Conclusion
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
Instagram: https://www.instagram.com/edureka_lea...
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Basics of Object Oriented Programming in PythonSujith Kumar
The document discusses key concepts of object-oriented programming (OOP) including classes, objects, methods, encapsulation, inheritance, and polymorphism. It provides examples of classes in Python and explains OOP principles like defining classes with the class keyword, using self to reference object attributes and methods, and inheriting from base classes. The document also describes operator overloading in Python to allow operators to have different meanings based on the object types.
This document provides step-by-step instructions for installing Python on Linux. It discusses selecting a Python version, downloading the installer from python.org, extracting and configuring the installer, making and installing Python, and testing the installation by printing "Hello World!". The instructions cover installing both Python 2 and Python 3 on Ubuntu systems.
This document provides instructions for installing Python version 2 or 3 on Windows. It explains that Python is commonly used for machine learning and deep learning. The user should select the version based on compatibility with their intended projects. The steps then outline downloading the installer from python.org, selecting options during installation like adding to the system PATH, and testing the installation by checking the version and running a simple print command in the terminal.
Python is a versatile, object-oriented programming language that can be used for web development, data analysis, and more. It has a simple syntax and is easy to read and learn. Key features include being interpreted, dynamically typed, supporting functional and object-oriented programming. Common data types include numbers, strings, lists, dictionaries, tuples, and files. Functions and classes can be defined to organize and reuse code. Regular expressions provide powerful string manipulation. Python has a large standard library and is used widely in areas like GUIs, web scripting, AI, and scientific computing.
This document provides an overview of the Python programming language. It discusses Python's history and evolution, its key features like being object-oriented, open source, portable, having dynamic typing and built-in types/tools. It also covers Python's use for numeric processing with libraries like NumPy and SciPy. The document explains how to use Python interactively from the command line and as scripts. It describes Python's basic data types like integers, floats, strings, lists, tuples and dictionaries as well as common operations on these types.
This presentation provides the information on python including the topics Python features, applications, variables and operators in python, control statements, numbers, strings, print formatting, list and list comprehension, dictionaries, tuples, files, sets, boolean, mehtods and functions, lambda expressions and a sample project using Python.
This document provides an overview of data visualization in Python. It discusses popular Python libraries and modules for visualization like Matplotlib, Seaborn, Pandas, NumPy, Plotly, and Bokeh. It also covers different types of visualization plots like bar charts, line graphs, pie charts, scatter plots, histograms and how to create them in Python using the mentioned libraries. The document is divided into sections on visualization libraries, version overview of updates to plots, and examples of various plot types created in Python.
This document provides an overview of Continuum Analytics and Python for data science. It discusses how Continuum created two organizations, Anaconda and NumFOCUS, to support open source Python data science software. It then describes Continuum's Anaconda distribution, which brings together 200+ open source packages like NumPy, SciPy, Pandas, Scikit-learn, and Jupyter that are used for data science workflows involving data loading, analysis, modeling, and visualization. The document outlines how Continuum helps accelerate adoption of data science through Anaconda and provides examples of industries using Python for data science.
This Edureka Python tutorial is a part of Python Course (Python Tutorial Blog: https://goo.gl/wd28Zr) and will help you in understanding what exactly is Python and its various applications. It also explains few Python code basics like data types, operators etc. Below are the topics covered in this tutorial:
1. Introduction to Python
2. Various Python Features
3. Python Applications
4. Python for Web Scraping
5. Python for Testing
6. Python for Web Development
7. Python for Data Analysis
This document provides an introduction to creating a simple calculator application using Python. It discusses that Python is a popular programming language used for web development, software development, mathematics, and system scripting. It then describes that the project will create a graphical user interface (GUI) calculator application using Python and the Tkinter library. Tkinter provides an object-oriented interface to create GUI applications in Python. The document outlines the system requirements, tools and technologies used, and includes a use case diagram for the calculator application.
This document provides an introduction to First Order Predicate Logic (FOPL). It defines FOPL as symbolized reasoning where sentences are broken down into subjects and predicates. FOPL is more expressive than propositional logic and allows representing almost any English sentence. It discusses features of FOPL such as generalization of propositional logic and more powerful representation. Applications of FOPL include presenting arguments, determining validity, and formulating theories. The document also defines key terms in FOPL such as constants, variables, functions, and predicates.
Python is an interpreted programming language created by Guido van Rossum in 1991. It has an elegant syntax, large standard library, and is used widely for data science, machine learning, web development, and more. Key Python libraries for data analysis include NumPy, pandas, and matplotlib. Pandas allows importing and cleaning data from files like CSVs, and matplotlib can be used to visualize and present analyzed data. For example, a program can use pandas to read baby name data from a CSV, find the most popular name with the highest birth count, and plot the results to clearly present the findings.
This document provides an overview of Pandas, a Python library used for data analysis and manipulation. Pandas allows users to manage, clean, analyze and model data. It organizes data in a form suitable for plotting or displaying tables. Key data structures in Pandas include Series for 1D data and DataFrame for 2D (tabular) data. DataFrames can be created from various inputs and Pandas includes input/output tools to read data from files into DataFrames.
Python An Introduction, A presentation Developed by Swarit Wadhe. This Slide Will Give you basic information about python (Origin, Codes and difference from other languages).
I hope you'll find this helpfull and if you do please share it with your fellows.
This Edureka Python Programming tutorial will help you learn python and understand the various basics of Python programming with examples in detail. Below are the topics covered in this tutorial:
1. Python Installation
2. Python Variables
3. Data types in Python
4. Operators in Python
5. Conditional Statements
6. Loops in Python
7. Functions in Python
8. Classes and Objects
Best Data Science Ppt using Python
Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data.
The document provides an introduction to Python programming. It discusses key concepts like variables, data types, operators, and sequential data types. Python is presented as an interpreted programming language that uses indentation to indicate blocks of code. Comments and documentation are included to explain the code. Various data types are covered, including numbers, strings, booleans, and lists. Operators for arithmetic, comparison, assignment and more are also summarized.
Installing Anaconda Distribution of PythonJatin Miglani
This document provides an overview of Anaconda, how it differs from a standard Python distribution, and how to install and use it. Anaconda is an open-source distribution of Python and R that includes over 1,000 data science packages to simplify package management. It uses the conda package manager to handle environments and installation of packages from various repositories. The document outlines how to install Anaconda, use conda commands to manage packages and environments, and integrate Anaconda with the PyCharm IDE.
The document provides an introduction to Python programming. It discusses installing and running Python, basic Python syntax like variables, data types, conditionals, and functions. It emphasizes that Python uses references rather than copying values, so assigning one variable to another causes both to refer to the same object.
5 Simple Steps To Install Python On Windows | Install Python 3.7 | Python Tra...Edureka!
** Python Certification Training: https://www.edureka.co/python **
This Edureka tutorial on Installing Python on Windows Tutorial covers all the aspects of installing and setting up Python to write code in. It is pretty simple and straightforward to setup Python completely in Windows as shown.
Following topics are covered in this PPT:
Agenda
Introduction to Python
Popularity of Python
Why should you learn Python?
Installing Python
Python Development Environments
Conclusion
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
Instagram: https://www.instagram.com/edureka_lea...
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Basics of Object Oriented Programming in PythonSujith Kumar
The document discusses key concepts of object-oriented programming (OOP) including classes, objects, methods, encapsulation, inheritance, and polymorphism. It provides examples of classes in Python and explains OOP principles like defining classes with the class keyword, using self to reference object attributes and methods, and inheriting from base classes. The document also describes operator overloading in Python to allow operators to have different meanings based on the object types.
This document provides step-by-step instructions for installing Python on Linux. It discusses selecting a Python version, downloading the installer from python.org, extracting and configuring the installer, making and installing Python, and testing the installation by printing "Hello World!". The instructions cover installing both Python 2 and Python 3 on Ubuntu systems.
This document provides instructions for installing Python version 2 or 3 on Windows. It explains that Python is commonly used for machine learning and deep learning. The user should select the version based on compatibility with their intended projects. The steps then outline downloading the installer from python.org, selecting options during installation like adding to the system PATH, and testing the installation by checking the version and running a simple print command in the terminal.
Python is an old programming language that has gained new popularity for machine learning. It exists in two versions, Python 2 and Python 3. The tutorial explains how to install both versions on a Mac by downloading them from python.org, running through an interactive installation process, and testing the installation by running sample Python code in the terminal.
This document provides instructions for setting up Python on Windows 10. It assumes the user has basic privileges on their computer. The steps outlined are for beginner Python users. It discusses downloading the correct Python version from python.org, installing it with default settings, and verifying the installation. It also covers installing additional Python packages both online and offline using pip and downloading source/wheel files. The document provides examples of installing common packages like NumPy, Pandas, and NLTK individually and multiple packages at once using a requirements.txt file.
How to download and install Python - lesson 2Shohel Rana
We will follow some steps to complete the installation process of Python.
1. Download the Python installer from Python website.
2. By double clicking install it.
3. Set the path for Python
4. Check Python is working very well.
5. If you missed the path setting for Python, then uninstall it and re install Python.
How to setup Pycharm environment for Odoo 17.pptxCeline George
Setting up a development environment for odoo using pycharm is highly preferred by odoo developers to develop and debug odoo modules and other related functionalities .
The document provides instructions for installing Python and Visual Studio Code (VS Code) on a Windows system. It includes steps to download the latest Python version from python.org, select the Windows installer, and install Python on the C:\Python path. It also gives directions to download VS Code from the official website, install Python and Code Runner extensions, and test a sample API request code in a new VS Code file using the Requests library.
The document provides instructions for installing Python and Visual Studio Code (VS Code) on a Windows system. It includes steps to download the Python installer from python.org, select the latest version, and install it on the C: drive. It also describes downloading VS Code from the official website, installing Python and Code Runner extensions, and provides a code sample to test an API using the requests module.
This explains the following questions.
1. How to install Aptana in Windows 8 64 bit os?
2. How to install Python in Windows 8 64 bit os?
3. How to install Django in Windows 8 64 bit os?
4. How to run a sample application in Django in Windows 8 64 bit os?
This will be useful for candidates who are learning Django framework.
Step-by-Step Instructions on How to Install Python 3Hedaro
Step-by-Step Instructions on How to Install Python 3
http://www.hedaro.com/install
Who this book is written for:
If you are looking for instructions on how to get Python 3 installed on your computer then this book is for you.
What is included in the book
This book provides you with very detailed step-by-step instructions on how to install Python 3 and a bunch of other Python libraries on your laptop.
How to install Python
How update Python using the Command Prompt
How to update Python libraries
How to install Python libraries
How to delete Python libraries
BONUS: Cheat Sheet included
How to remove old packages that are not being used
How to get a list of installed Python packages
How to use easy_install or pip as a fall back to conda
This document provides instructions for setting up Python for a GIS programming course. It includes downloading Python and a text editor, setting environment variables to add Python to the system path, using pip to install additional packages, and joining a Slack channel to ask questions and submit assignments. Students are assigned to download Python, a text editor, set environment variables, test Python commands, take screenshots of the setup process, join Slack, and upload their first assignment there.
This document provides instructions for installing Python 2.7.9 and Anaconda on Windows, OSX, and Linux systems. It describes downloading the Python 2.7.9 installer from the Python website and running it to complete the installation on Windows. It notes that Python comes pre-installed on OSX and Linux systems. It also gives directions for downloading and installing the Anaconda installer from the Continuum Analytics website and running it with default settings on Windows, OSX, and Linux.
This document discusses installing and getting started with Python. It provides an overview of Python, including its uses and features. It then describes how to download the Python distribution, complete the installation process, and work in Python interactively or by writing script files. Potential shortcomings are also mentioned. The goal is to introduce readers to Python and guide them through setting it up on their system so they can begin working with the programming language.
The document provides tips and tricks for customizing and getting more out of the Ubuntu operating system, including how to use applications like Wine to run Windows programs, tools for updating software and receiving notifications of updates, how to edit images with GIMP, and ways to change the desktop theme, mouse cursor, and enable the rotating cube desktop effect.
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)Rebecca Bilbro
To honor ten years of PyData London, join Dr. Rebecca Bilbro as she takes us back in time to reflect on a little over ten years working as a data scientist. One of the many renegade PhDs who joined the fledgling field of data science of the 2010's, Rebecca will share lessons learned the hard way, often from watching data science projects go sideways and learning to fix broken things. Through the lens of these canon events, she'll identify some of the anti-patterns and red flags she's learned to steer around.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of May 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
Build applications with generative AI on Google CloudMárton Kodok
We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.
2. For Windows OS:
To check whether your OS already has python in your system or not
Go to cmd terminal as shown and type: python
If it is not preinstalled If it is already preinstalled
Python Installation
3. If it is not preinstalled go to: python.org > scroll down > click on “Latest:
Python 3. x”
Select the downloader as per your OS
Here in my case I have the Windows 64 bit OS, so I clickd on the
highlighted.
Python Installation
4. Once the .exe file is downloaded > open the file > Run
1st
2nd
Python Installation
5. The setup will proceed after asking permission from admin, when setup is
done close the setup window and go back to your cmd and check whether it
is showing the installed python or not.
Python Installation
6. As we can see from the below screenshot the updated python version is
installed.
Now we’ll move on to Jupyter notebook installation.
Python Installation
7. We’ll install jupyter notebook by pip in python interpreter
Go to jupyter.org > click on “Install”
You’ll see the cmd to be used to install jupyter notebook using pip in python
Jupyter notebook Installation
8. Go back to cmd > “python –m pip install jupyter“
Now it will collect all the libraries, packages that
are part of this and install jupyter on your
machine.
Once it is installed you’ll see a message installed
successfully.
If your pip is not upgraded you can use the
following command
”python -m pip install --upgrade pip”
And to check whether your jupyter notebook is
installed or not, again type the cmd:
“python –m pip install jupyter”
Jupyter notebook Installation
9. Now to run the jupyter notebook
Go to cmd prompt and type
“jupyter notebook”
And the jupyter notebook will open in a selected browser, preferably
Chrome.
And if you want to open a jupyter notebook to a specific path then you
can copy paste the path and write ‘jupyter notebook’ after that
E.g.
Jupyter notebook Installation