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Vue Tips Collection [Michael Thiessen ] [EBook]

VueMastery - Querying with GraphQL

FireShip - The Vue Firebase Project Course

Build scalable & performant full-stack serverless applications (Appsync Masterclass)

Vue 3 Fundamentals | Beginners Guide 2023

The Vue 3 Bootcamp - The Complete Developer Guide

Learn how to build a Django-powered content engine that leverages AWS S3 for nearly unlimited amount of stored videos, images, files, and more. This content engine will also be extra private and secure thanks to Twingate's effective approach to sharing assets behind a next-generation private network.
We start by automating the process of containerizing our Django application without writing a single Dockerfile. This means, we just focus on our code without learning Docker much like you would with a PaaS (e.g. Heroku). This is possible thanks to the great cloud-native tool known as Buildpacks and it's simple on GitHub Actions.
With Kubernetes and Twingate, we will provide provide and secure&nbsp;local&nbsp;access to&nbsp;any&nbsp;resource we decide: Django project, databases, and much more depending on what containerized-app you want to use.
Once this foundation is laid, we'll build out our Django project using cutting edge tools like HTMX and TailwindCSS to provide a fast, functional, and effective way to deliver a modern user experience without the overhead of writing JavaScript or CSS.
The last major piece is getting large file uploads to work. This means we'll be learning all about how to use the official Amazon S3 package for Python known as Boto3. With Boto3, we will pre-sign files so we can download them, upload them, and delete them. In addition to Boto3, we write pure JavaScript to handle the uploading process (using functions like Fetch and XMLHttpRequests).
This course is a juggernaut and we are excited to share it with you. And guess what? Thanks to Twingate, this entire course is already yours (just login and add it to your library).
Are you ready to begin? Let's do this!
<h3 id="references">References</h3>
<ul>
<li>Sign up for&nbsp;<a href="https://www.twingate.com/?utm_source=youtube&amp;utm_medium=referral&amp;utm_campaign=CodingEntrepreneurs">Twingate</a></li>
<li>Course GitHub &amp; Code&nbsp;<a href="https://github.com/codingforentrepreneurs/content-engine">here</a></li>
<li>Django Auto Container&nbsp;<a href="https://github.com/codingforentrepreneurs/django-auto-container">here</a></li>
</ul>
<h3 id="helpfulresources">Helpful Resources</h3>
<ul>
<li>Django on Docker&nbsp;<a href="https://cfe.sh/blog/django-on-docker">guide</a></li>
<li>Docker &amp; Docker Compose&nbsp;<a href="https://cfe.sh/projects/docker-and-docker-compose">tutorial series</a>:</li>
<li>Github Actions&nbsp;<a href="https://cfe.sh/blog/django-github-actions">guide</a>:</li>
<li>Django &amp; Kubernetes project&nbsp;<a href="https://github.com/codingforentrepreneurs/Django-Kubernetes">code</a></li>
</ul>

Content Engine 🔥

Content Engine - Codingforentrepreneurs.com

<div data-purpose="safely-set-inner-html:description:description">
Do you want to learn Machine Learning but don&rsquo;t know where to start?
Have you been looking for a&nbsp;beginner-friendly course&nbsp;that will equip you with powerful tools for your career?
You&rsquo;ve come to the right place!
This is Machine Learning in Python Level 1... and we will help you get started.
My name is Kirill Eremenko, I&rsquo;m a Data Science instructor with over 7 years of experience, and together with my co-instructor Hadelin de Ponteves we have&nbsp;taught over 2M students Worldwide.
And now, we&rsquo;ve created this course to help YOU get on track with Machine Learning and start applying it in YOUR career.
This course has 3 main sections:
First, we will dive into Regression, where we will learn to predict continuous variables and we will cover foundational concepts like&nbsp;Simple and Multiple Linear Regression, Ordinary Least Squares, Testing your Model, R-Squared and Adjusted R-Squared.
In the second section you will master Logistic Regression, which is by far the most popular model for Classification. We will learn all about Maximum Likelihood, Feature Scaling, The Confusion Matrix, Accuracy Ratios... and you will&nbsp;build your very first Logistic Regression!
The third and final section is all about Clustering. We will investigate the concepts of unsupervised learning and you will practice using&nbsp;K-Means Clustering to discover previously unseen patterns&nbsp;in your data.
Sound exciting?
Well, in this course not only will you learn the theory behind all of these Machine Learning models, but you will also&nbsp;practice applying them in different scenarios&nbsp;so that you are prepared for the Real World.
Plus, you will get&nbsp;Python code templates&nbsp;which you can download and keep. These are invaluable tools which you can apply in your own projects right away.
So, what are you waiting for?
Sign up today&nbsp;and take your career to the next level with Machine Learning!
</div>
<div class="styles--audience--2xuzW" data-purpose="target-audience">
<h2 class="ud-heading-xl styles--audience__title--1qhlO">Who this course is for:</h2>
<ul class="styles--audience__list--16EaN">
<li>Anyone interested in Data Science</li>
<li>Anyone who wants to become a Data Scientist</li>
<li>Anyone interested in Machine Learning</li>
<li>Anyone who wants to become a ML or AI engineer</li>
<li>Data Science professionals</li>
<li>Machine Learning professionals</li>
<li>Anyone who wants to add Machine Learning to their CV or career toolkit</li>
</ul>
<h2>What you'll learn</h2>
<ul>
<li>Machine Learning</li>
<li>The Machine Learning Process</li>
<li>Regression</li>
<li>Ordinary Least Squares</li>
<li>Simple Linear Regression</li>
<li>Splitting your data into a Training set and a Test set</li>
<li>Multiple Linear Regression</li>
<li>R-Squared</li>
<li>Adjusted R-Squared</li>
<li>Classification</li>
<li>Maximum Likelihood</li>
<li>Feature Scaling</li>
<li>Confusion Matrix</li>
<li>Accuracy</li>
<li>Clustering</li>
<li>K-Means Clustering</li>
<li>The Elbow Method</li>
<li>K-Means++</li>
<li>Build Machine Learning models in Python</li>
<li>Make Predictions</li>
</ul>
<h2 class="ud-heading-xl requirements--title--2wsPe" data-purpose="requirements-title">Requirements</h2>
<ul class="ud-unstyled-list ud-block-list">
<li>
<div class="ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm">
<div class="ud-block-list-item-content">Every single line of code will be fully explained so there are no prerequisites for coding skills</div>
</div>
</li>
<li>
<div class="ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm">
<div class="ud-block-list-item-content">This is a foundational course, so no prior knowledge of Data Science is required</div>
</div>
</li>
<li>
<div class="ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm">
<div class="ud-block-list-item-content">Some high-school level mathematics knowledge is recommended but not required</div>
</div>
</li>
<li>
<div class="ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm">
<div class="ud-block-list-item-content">We use Google Colab for coding in Python which is very intuitive, but you can also use Jupyter or another IDE</div>
</div>
</li>
</ul>
</div>

Machine Learning in Python ❤️‍🔥

Beginner Machine Learning in Python + ChatGPT Prize [2024] - Udemy

This Machine Learning Essentials course offers a comprehensive introduction to the world of AI and ML, covering the maths behind essential algorithms and their implementation in Python. With 8+ hands-on projects, this course is designed for beginners as well as proficient programmers. Enroll today and learn logistic regression, linear regression, principal component analysis, Naive Bayes, decision trees, bagging and boosting, K-NN, K-Means, neural networks, and much more!
&nbsp;
<h2>What you'll Learn</h2>
<ul>
<li>Kick off the universe of AI and ML</li>
<li>Maths of Machine Learning</li>
<li>Regression and Classification Methods</li>
<li>Straight and Strategic Regression</li>
<li>K-Nearest Neighbors, K-Means</li>
<li>Naive Bayes, Text Classification</li>
<li>Decision Trees and Random Forests</li>
<li>Ensemble Learning - Bagging and Boosting</li>
<li>Dimensionality Reduction</li>
<li>Neural Networks</li>
<li>8+ Hands on Projects</li>
</ul>
&nbsp;
<h2>Prerequisites</h2>
Python Programming
Basics of Numpy, Pandas, Matplotlib
<h2>Description</h2>
Peruse to kick off the universe of Machine Learning and Computerized reasoning?
&nbsp;
This involved course is intended for outright amateurs as well concerning capable developers who need kickstart Machine Learning for tackling genuine issues. You will figure out how to work with data, and train models equipped for making "insightful decisions"
Data Science has one of the most compensating position of the 21st 100 years and fortune-500 tech organizations are spending intensely on data researchers! Data Science as a profession is extremely fulfilling and offers quite possibly of the most significant compensation on the planet. Unlike different courses, which cover just library-executions this course is intended to give you a strong groundwork in Machine Learning by covering maths and execution without any preparation in Python for most measurable methods.
This comprehensive course is educated by Prateek Narang and Mohit Uniyal, who famous teachers as well as have worked in Computer programming and Data Science domains with organizations like Google. They have shown great many understudies in a few on the web and in-person courses over last 3+ years.
&nbsp;
We are giving you this course to you for a portion of its unique expense! This is activity arranged course, we dig into hypothesis as well as spotlight on the down to earth viewpoints by building 8+ projects.
&nbsp;
With over 170+ excellent video addresses, straightforward clarifications and complete code archive this is one of the most detailed and strong course for learning data science.
&nbsp;
A portion of the points that you will learn in this course.
<ul>
<li>Calculated Regression</li>
<li>Straight Regression</li>
<li>Head Part Examination</li>
<li>Naive Bayes</li>
<li>Decision Trees</li>
<li>Bagging and Boosting</li>
<li>K-NN</li>
<li>K-Means</li>
<li>Neural Networks</li>
</ul>
&nbsp;
A portion of the ideas that you will learn in this course.
Convex Enhancement
Overfitting as opposed to Underfitting
Bias Variance Tradeoff
Performance Metrics
Data Pre-processing
Feature Engineering
Working with numeric data, pictures and textual data
Parametric versus Non-Parametric Strategies
Pursue the course and take your initial move towards turning into a machine learning engineer! See you in the course!
Who this course is for:
Developers who are interested to about Machine Learning and Fake Intellgence
Working experts who need to fabricate a lifelong in data science
Engineers who needs to get familiar with another skill and fabricate ML based projects
College and understudies who need to fortify comprehension they might interpret Machine Learning
<h2>Teachers</h2>
Mohit Uniyal
Data Researcher and Coding Minutes Teacher
<ul>
<li>4.3 Teacher Rating</li>
<li>2,006 Reviews</li>
<li>15,087 Students</li>
<li>4 Courses</li>
</ul>
Mohit is a Data Researcher, programming teacher and co-maker at Coding Minutes. He has trained over 20000+ understudies in Machine Learning and AI throughout the course of recent long stretches of his educating experience. His mastery lies in Python, data science, machine learning and AI, and he has won numerous rivalries. He has been doing AI-based projects throughout the previous 4 years. He additionally drives the ML and Data Science Domain of Coding Minutes.
<h2>Prateek Narang</h2>
Teacher and Entrepreneur - Google, Coding Minutes, Scaler
<ul>
<li>4.4 Educator Rating</li>
<li>10,442 Reviews</li>
<li>81,058 Students</li>
<li>9 Courses</li>
</ul>
Prateek is famous programming teacher and an expert programmer having worked with Google previously, right now working with Scaler and made Coding Minutes to bring excellent courses at pocket agreeable valuing. He is known for his incredibly worked on clarifications that makes everybody experience passionate feelings for programming. He has over 5+ long stretches of showing experience and has trained more than 50,000 understudies in study hall bootcamps and online course at a well known bootcamp before. His ability lies in critical thinking, calculations, cutthroat programming and machine learning. His intuitive mario style at prateeknarang continue is adored by all. Large numbers of his ex-understudies are currently working in top item organizations like Apple, Google, Amazon, PayTm, Microsoft, Flipkart, Samsung, Adobe, DE Shaw, Codenation, Arcesium and that's only the tip of the iceberg.
Show more
4.2 course rating4 9 reviews
Minh Cong H.
Rating: 4.5 out of 52 weeks prior
MH
&nbsp;
howdy, might you at some point if it's not too much trouble, make slides like the C++ courses you have previously delivered? I found the dark background shade of the slides more eye-accommodating, and I can look at them for longer timeframes. I have taken your C++ course and have become acclimated with this organization. The white background with black text isn't really great for my nearsighted eyes, and I experience issues focusing on the material. I have likewise taken a cycle of your machine learning course, however the white background utilized in that course makes my eyes tire more quickly than expected, making it hard for me to think and finish the course. I actually appreciate the great pictures utilized in your C++ course.Besides, the captions of the Coding Minutes courses are frequently mistaken, and I truly trust that you can fix them quickly. It is extremely challenging for me to learn without exact captions, I'm learning at a sluggish speed and not completely retaining the material because of the issue of erroneous subtitles.Thank to such an extent!
&nbsp;
Shubham G.
Rating: 5.0 out of 5 3 weeks prior
&nbsp;
Ideal beginning for amateurs.. A seriously broad scope of points covered ... Explains the working and instinct behind each... Code discussions...Community support...Great Connected explainations with genuine world for fairly troublesome themes like slope plunge, etc..Must suggest for novices. :)
&nbsp;
Manya K.
Rating: 5.0 out of 5 2 months prior
&nbsp;
This is simply wonderful!! It assisted me with fostering my advantage in MLI truly waited excessively lengthy for this.My semester project is most certainly profiting from the material of this course, which has made me very cheerful and fulfilled overall.The coaches of this course merit a genuine thank you. The most expected course ever is this one.
&nbsp;
Smriti R.
Rating: 5.0 out of 5 2 months prior
&nbsp;
it's so cool and reasonable. amazing I presume
Useful links:
<ul>
<li>Course link: <a href="https://www.udemy.com/course/machine-learning-essentials-with-maths-in-python/" target="_new">https://www.udemy.com/course/machine-learning-essentials-with-maths-in-python/</a></li>
<li>Prateek Narang's LinkedIn profile: <a href="https://www.linkedin.com/in/prateek-narang/" target="_new">https://www.linkedin.com/in/prateek-narang/</a></li>
<li>Mohit Uniyal's LinkedIn profile: <a href="https://www.linkedin.com/in/mohit-uniyal-41a7a9120/" target="_new">https://www.linkedin.com/in/mohit-uniyal-41a7a9120/</a></li>
<li>Python Programming tutorial: <a href="https://www.tutorialspoint.com/python/index.htm" target="_new">https://www.tutorialspoint.com/python/index.htm</a></li>
<li>Numpy tutorial: <a href="https://numpy.org/doc/stable/user/quickstart.html" target="_new">https://numpy.org/doc/stable/user/quickstart.html</a></li>
<li>Pandas tutorial: <a href="https://pandas.pydata.org/docs/user_guide/10min.html" target="_new">https://pandas.pydata.org/docs/user_guide/10min.html</a></li>
<li>Matplotlib tutorial: <a href="https://matplotlib.org/stable/tutorials/index.html" target="_new">https://matplotlib.org/stable/tutorials/index.html</a></li>
</ul>

Machine Learning Essentials 🚀

Machine Learning Essentials (2023)

Enhance your design process with the latest Figma features! Join the Figma for Developers, v2 workshop by FrontendMasters. Master Developer Mode, Auto Layout, interactive components, and more with expert guidance from Steve Kinney. Perfect for UI/UX designers and frontend developers
<h2>Key Takeaways</h2>
By participating&nbsp;along&nbsp;with us in the workshop, you'll learn:
<ul>
<li>Mastering Developer Mode for efficient design navigation</li>
<li>Utilizing improved Auto Layout for dynamic designs</li>
<li>Creating interactive components for advanced prototyping</li>
<li>Leveraging enhanced collaboration features for team projects</li>
<li>Integrating Figma with tools like Storybook and VS Code</li>
<li>Generating effective code snippets for development</li>
<li>Exploring new prototyping and animation features</li>
<li>Keeping up-to-date with the latest design tools in Figma</li>
</ul>
<h3>Is This Workshop for Me?</h3>
Frontend developers and UI/UX designers looking to deepen their understanding of Figma&rsquo;s latest features for a more efficient and collaborative design process.
&nbsp;
<h2>&nbsp;</h2>
<h2>Workshop Details</h2>
This workshop is tailored for frontend developers, focusing on the latest features in Figma, including Developer Mode, improved Auto Layout, and interactive components. It provides insights into integrating Figma with development workflows and explores new prototyping and animation features, enhancing the design-to-code process.
<h3>Any Prerequisites?</h3>
<ul>
<li>Basic understanding of UI/UX design principles</li>
<li>Familiarity with Figma&rsquo;s basic functionalities</li>
</ul>
&nbsp;
<h2>Event Details</h2>
<h3>What</h3>
<ul>
<li>One&nbsp;Full Day Workshop&nbsp;Session</li>
<li>Replay Videos (available immediately)</li>
</ul>
<h3>When</h3>
<ul>
<li>April 16, 2024 -&nbsp;9:30am&nbsp;to&nbsp;5:30pm&nbsp;Central Daylight Time</li>
</ul>
<h3>Where</h3>
<ul>
<li>Option 1: Attend online on our full HD live stream</li>
<li>Option 2: Attend in-person at HQ in Minneapolis, MN</li>
</ul>
&nbsp;
<h2>Daily Schedule</h2>
Spend a full day building prototypes and UI components in Figma with Steve Kinney.
<ul>
<li>9:30AM</li>
<li>Introduction to Figma</li>
<li>10:00AM</li>
<li>Working with Frames</li>
<li>10:30AM</li>
<li>Selecting and Inspecting</li>
<li>11:00AM</li>
<li>Working with Styles</li>
<li>11:30AM</li>
<li>Constraints and Layouts</li>
<li>12:00PM</li>
<li>Lunch</li>
<li>1:00PM</li>
<li>Creating Components and Variants</li>
<li>2:00PM</li>
<li>Developer Mode in Figma</li>
<li>2:30PM</li>
<li>Prototyping with Figma</li>
<li>3:00PM</li>
<li>Integration of Figma with Development Tools (Storybook and VS Code)</li>
<li>3:30PM</li>
<li>Generating Effective Code Snippets for Development</li>
<li>4:00PM</li>
<li>Interactive Components and Advanced Prototyping</li>
</ul>
<h2>Your (Awesome) Instructor</h2>
<h3><a class="editor-rtfLink" href="https://frontendmasters.com/teachers/steve-kinney/" target="_blank" rel="noopener">Steve Kinney</a></h3>
Steve is the front-end architect at Temporal. Previously, he was the front-end architect at Twilio and SendGrid. He is the director emeritus and founder of the front-end engineering program at the Turing School for Software and Design in Denver, Colorado &mdash; a non-profit developer training program. In a previous life, Steve was a New York City public school teacher. He taught special education and web development in Manhattan, Brooklyn, and Queens. He currently lives in Denver, Colorado
Useful Links:
<ol>
<li><a href="https://www.figma.com/" target="_new" rel="noreferrer">Figma Documentation</a></li>
</ol>

Figma for Developers ❤️

Figma for Developers, v2 [FrontendMasters]

Figma for Developers, v2 [FrontendMasters]

Key Takeaways

Is This Workshop for Me?

Workshop Details

Any Prerequisites?

Event Details

What

When

Where

Daily Schedule

Your (Awesome) Instructor

Steve Kinney

Harry Potter

Leave a comment

0 Comment

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How to download ??

This site is hosted on Digital Ocean

Get $200 credit Instantly

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( Take advantage of free credits 👇 )

Related Posts

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Figma for Developers, v2 [FrontendMasters]

Key Takeaways

Is This Workshop for Me?

Workshop Details

Any Prerequisites?

Event Details

What

When

Where

Daily Schedule

Your (Awesome) Instructor

Steve Kinney

Harry Potter

Leave a comment

0 Comment

Membership Plans

How to download ??

This site is hosted on Digital Ocean

Get $200 credit Instantly

Offer available for limited time ( Take advantage of free credits 👇 )

Related Posts

Tags

Offer available for limited time
( Take advantage of free credits 👇 )