As a Front-End and Web Developer Engineer, I specialize in creating engaging and responsive user interfaces. My
expertise includes developing dynamic web applications using HTML, CSS, JavaScript, and frameworks like React. I am dedicated to continuous learning and applying new technologies to enhance user experiences and solve
complex development challenges.
Anwar is a great front end developer. I’ve been thoroughly impressed with the insights and visualizations provided by this platform. I would highly recommend him
to anyone who is looking for a web development.
Jane Doe
Working with this web development team has been a game-changer for our business. Their expertise in designing and
building our website has helped us enhance our online presence and directly impact our success
Projects
I am interested in web development and design. I am working on developing dynamic websites and web applications
utilizing modern technologies.
Involvement in large-scale web projects and responsive design is my focus.
Difference between Arguments and Parameters in python
The terms arguments and parameters are often used interchangeably, But they do have slightly difference in these both terms.
A parameter is a variable that is defined in the function signature or method definition. It specifies what kind of value the function or method expects to receive when it is called.
The payload in HTTPS is the data that is sent or received with the HTTPS request. It is usually encrypted by the SSL/TLS protocol to ensure security and privacy. The payload can be in different formats, such as JSON, XML, or plain text.
The payload can be sent with different HTTP methods, such as POST or PUT, which support body data. The payload is included in the body of the request.
This course is part of the IBM Program Certificate in Data Science. This course will attempt to explain the foundational concepts and techniques of Data Science. It will help you to understand the important roles that statistics, probability, mathematics, and computer science play in the field of Data Science.
Python Programming: introduces Python, a popular programming language for data analysis and machine learning. perform statistical analysis, and build predictive models using Python libraries like NumPy, Pandas, and scikit-learn.
manipulation: Participants learn how to manipulate data
Notebooks: Jupyter Notebooks are interactive coding environments that enable data scientists to create and share documents containing code, visualizations, and explanatory text.
SQL and Relational Databases: Understanding SQL (Structured Query Language) is crucial for working with large datasets stored in relational databases.
Open Source Tools: The course highlights various open-source tools widely used in the data science community.
Play the role of a Data Scientist / Data Analyst working on a real project.
Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.
Apply Python fundamentals, Python data structures, and working with data in Python.
Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.
Machine learning with Tree-Based model in Python
Decision trees are supervised learning models used for problems involving classification and regression. Tree models present a high flexibility that comes at a price: on one hand, trees are able to capture complex non-linear relationships; on the other hand, they are prone to memorizing the noise present in a dataset. By aggregating the predictions of trees that are trained differently, ensemble methods take advantage of the flexibility of trees while reducing their tendency to memorize noise.
This is bold and this is strong. This is italic and this is emphasized.
This is superscript text and this is subscript text.
This is underlined and this is code: for (;;) { ... }. Finally, this is a link.
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i = 0;
while (!deck.isInOrder()) {
print 'Iteration ' + i;
deck.shuffle();
i++;
}
print 'It took ' + i + ' iterations to sort the deck.';
