- 👋 Hi, I’m @khokhriya
- 👀 I’m interested in Python Development
- 🌱 I’m currently learning AI and Machine Learning
- 💞️ I’m looking to collaborate on Latest technology
- 📫 How to reach me ...
khokhriya Goto Github PK
Name: Dhruv Khokhriya
Type: User
Name: Dhruv Khokhriya
Type: User
Module-1 introduces basic Machine Learning concepts, tasks, and workflow using an example classification problem based on the K-nearest neighbors method, and implemented using the scikit-learn library. Module-2 delves into a wider variety of supervised learning methods for both classification and regression. Module-3 covers evaluation and model selection methods that you can use to help understand and optimize the performance of your machine learning models. Module-4 covers more advanced supervised learning methods that include ensembles of trees (random forests, gradient boosted trees), and neural networks (with an optional summary on deep learning). You will also learn about the critical problem of data leakage in machine learning and how to detect and avoid it.
An overview of client-side web UI frameworks, in particular Bootstrap 4. Grids and responsive design, Bootstrap CSS and JavaScript components. About CSS preprocessors, Less and Sass. Basics of Node.js and NPM and task runners like Grunt and Gulp.
IBM Coursera Capstone
This Course taught me to fetch and process data from services on the Internet. It covers Python list comprehensions processing deeply nested data. learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs.
Deep Neural Networks with PyTorch
A Python application and tutorial that use Flask framework to provide a REST API to receive requests from the UI. The API then persists the data to a Cloudant database.
The basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python.
Jupiter Notebooks with code, Assignments, Study Materials of IBM Data Science Professional Certificate.
Basics of machine learning using an approachable, and well-known programming language, Python.A general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.
Manipulation of files and processes on your computer’s operating system. Regular expressions-- a very powerful tool for processing text files. Execute Python locally, and organize and use code across different Python files. Read and write different types of files, and use sub processes and input streams. Bash scripting. Automatic testing. Set up your own developer environment in your machine.
Introduction to Deep Learning & Neural Networks with Keras
Config files for my GitHub profile.
In this project, it is required to explore, segment, and cluster the neighborhoods in the city of Toronto. What is interesting about the field of data science is that each project can be challenging in its unique way, so we need to learn to be agile and refine the skill to learn new libraries and tools quickly depending on the project.
The Python Imaging Library, which is known as PIL or PILLOW, is the main library we use in python for dealing with image files.
This course introduces classes, instances, and inheritance. You will learn how to use classes to represent data in concise and natural ways. You'll also learn how to override built-in methods and how to create "inherited" classes that reuse functionality. You'll also learn about how to design classes. Finally, you will be introduced to the good programming habit of writing automated tests for their own code.
This course took me from zero to programming in Python in a matter of hours—no prior programming experience necessary! I Learnt Python fundamentals, including data structures and data analysis, completing hands-on exercises throughout the course modules, and created a final project to demonstrate my new skills.
In this project, the task is to build a sentiment classifier, which will detect how positive or negative each tweet is. We will create a csv file, which contains columns for the Number of Retweets, Number of Replies, Positive Score (which is how many happy words are in the tweet), Negative Score (which is how many angry words are in the tweet), and the Net Score for each tweet. At the end, we upload the csv file to Excel or Google Sheets, and produce a graph of the Net Score vs Number of Retweets.
Python_Developer_Portfolio hello dera
Scalable Machine Learning on Big Data using Apache Spark
In this course, you'll explore the basic structure of a web application, and how a web browser interacts with a web server. You'll be introduced to the Hypertext Transfer Protocol (HTTP) request/response cycle, including GET/POST/Redirect. You'll also gain an introductory understanding of Hypertext Markup Language (HTML), as well as the overall structure of a Django application. We will explore the Model-View-Controller (MVC) pattern for web applications and how it relates to Django. You will learn how to deploy a Django application using a service like PythonAnywhere so that it is available over the Internet.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.