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Stock Market Trading: The Complete Technical Analysis Course

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Algotrading For Beginners With Technical Analysis

Master Class : Smart Money Concepts - Key Level strategiesLevel 3

ZERO TO HERO PROGRAM to Build Your Entire Trading Career in Stock Market, Commodity market & Forex Market

Cuvette - Placement Guarantee Course - April Batch

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

Build WhatsApp clone w video calls Mern stack socket io 2023

MERN Invoice Web App with Docker,NGINX and ReduxToolkit

Build Facebook clone with REACT JS AND THE MERN STACK

Node.js, Express, MongoDB & More: The Complete Bootcamp

Build The Best Ecommerce Website Ever With React Js Next Js

The Full Stack Web Development Bootcamp 2023 - MERN STACK

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As you go down the rabbit hole of building Python Web Applications you inevitably start to wonder how this is all going to run in a live, production, environment. This series aims to answer this question by deploying a basic Python Web Application from scratch to Linode's powerful and cost-effective service. Once you understand the fundamentals from scratch, you can learn to deploy using more scalable and powerful solutions (like Terraform, Ansible, and others).
Get started with a $100 credit to your account by going&nbsp;<a href="https://www.linode.com/cfe">here</a>.
References:
<ul>
<li><a href="https://github.com/codingforentrepreneurs/deploy-fastapi-from-scratch">Code</a></li>
</ul>
This series was created in partnership with Linode.
<h4>Lessons:</h4>
1 - Welcome 2 - Walkthrough - What were doing and why 3 - Recommendations before Starting 4 - Provisioning a Linode 5 - Your First Secure Connection 6 - Passwordless SSH with SSH Public Keys 7 - Configure new User &amp; Group Permissions 8 - Install nginx and UFW 9 - Why We Need Version Control 10 - Git Basics 11 - Git Remote Host on Linode Part 1 12 - Git Remote Host on Linode Part 2 13 - Install Python &amp; Use a Virtual Environment 14 - Production Ready Virtual Environment 15 - Our First Python FastAPI Web App 16 - Nginx for Web Server - Part 1 17 - Supervisor Part 1 18 - Deploy &amp; Solve 19 - Provisioning a PostgreSQL Server 20 - Setup Postgres Database 21 - Bind &amp; Configure Postgresql to the Server 22 - Provision &amp; Configure a Redis Server 23 - Nginx Load Balancer 24 - Custom Domain Name 25 - Implementing HTTPs on our Custom Domain with Lets Encrypt 26 - Prod &amp; Dev Database Servers 27 - Environment Variables on Webapp Servers 28 - Environment Variables in FastAPI 29 - Data Validation with pydantic 30 - Test Pydantic Models with pytest 31 - Database Configuration 32 - Database Model with SQLAlchemy 33 - Schema Models as Views 34 - Integrating the Database CRUD Methods with API Endpoints 35 - Push into Production 36 - Thank you for watching

Web Apps from Scratch 🔥

Deploy Python Web Apps from Scratch - Coding for Entrepreneurs

Dive into Machine Learning in JS with FrontendMasters. Master machine learning fundamentals, create projects with TensorFlow.js, and explore image and audio recognition. Perfect for front-end developers looking to expand their skillset!
<h2>Key Takeaways</h2>
By participating&nbsp;along&nbsp;with us in the workshop, you'll learn:
<ul>
<li>Machine Learning Fundamentals</li>
<li>Use pre-trained models and understand transfer learning</li>
<li>Create projects with image and audio recognition</li>
<li>Create custom models and split training data between training and testing sets</li>
</ul>
<h3>Is This Workshop for Me?</h3>
Front-end developers with a basic understanding of JavaScript, who would like to expand their knowledge of what is possible to do with front-end technologies, and who would like to learn more about machine learning while using a programming language they&rsquo;re already familiar with.
&nbsp;
&nbsp;
<h2>Workshop Details</h2>
By the end of this course, developers will have a deeper understanding of machine learning,&nbsp;what&nbsp;is currently possible in JavaScript, and create 3 projects exploring TensorFlow.js features.
<h3>Any Prerequisites?</h3>
<ul>
<li>No prior knowledge of machine learning needed</li>
<li>Basic front-end knowledge and understanding of JavaScript (syntax, data structures, working with APIs)</li>
<li>Any operating system and code editor should do</li>
</ul>
&nbsp;
&nbsp;
<h2>Event Details</h2>
<h3>What</h3>
<ul>
<li>2 Full Day Workshop Sessions</li>
<li>Replay Videos (available immediately)</li>
</ul>
<h3>When</h3>
<ul>
<li>April 18 to 19, 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>
<h2>Daily Schedule</h2>
<h3>Day 1</h3>
<ul>
<li>9:30AM</li>
<li>Introduction to Machine Learning</li>
<li>10:30AM</li>
<li>Using Pre-Trained Models</li>
<li>12:00PM</li>
<li>Lunch</li>
<li>1:00PM</li>
<li>Setting up TensorFlow.js</li>
<li>2:00PM</li>
<li>Image Recognition Project</li>
</ul>
<h3>Day 2</h3>
<ul>
<li>9:30AM</li>
<li>Introduction to Transfer Learning</li>
<li>10:30AM</li>
<li>Image and Sound Recognition Project</li>
<li>12:00PM</li>
<li>Lunch</li>
<li>1:00PM</li>
<li>Making Your&nbsp;Own&nbsp;Model Project</li>
</ul>

Machine Learning in JS 🔥

Machine Learning in JS [FrontendMasters]

<h2>Courses in this path</h2>
<div class="row border-top difficulty-container active">
<div class="difficulty-header">
Beginner -&nbsp;Build your first PyTorch project, learning the underlying concepts behind the library and how it operates, and apply your knowledge in the Cloud.
1. Foundations of PyTorch
2. Building Your First PyTorch Solution
3. Using PyTorch in the Cloud: PyTorch Playbook
Intermediate -&nbsp;Apply PyTorch to common deep learning problem domains.
1. Building Deep Learning Models Using PyTorch
2. Image Classification with PyTorch
3. Style Transfer with PyTorch
4. Natural Language Processing with PyTorch
<div class="difficulty-header">
Advanced - Use PyTorch to create predictive analytics models, apply transfer learning techniques, and deploy and monitor your models in production.
</div>
1. Expediting Deep Learning with Transfer Learning: PyTorch Playbook
2. Predictive Analytics with PyTorch
3. Deploying PyTorch Models in Production: PyTorch Playbook
<h3>Experience</h3>
<ul>
<li>Machine Learning Literacy</li>
<li>Python Programming</li>
</ul>
</div>
</div>

Building Deep Learning Solutions ❤️‍🔥

Building Deep Learning Solutions with PyTorch - Pluralsight

Join the Complete Machine Learning and Data Science Bootcamp and become a skilled Data Scientist. Learn Python, Tensorflow, Pandas, deep learning, and more. Build real-world projects and gain the industry skills to land a job. Trusted by top tech companies like Google, Tesla, and Amazon
One of the most well known, profoundly appraised machine learning and data science bootcamps online. It's likewise the most current and forward-thinking. Ensured. You'll go from complete fledgling with no related knowledge to getting recruited as a Machine Learning Specialist this year.
You'll learn Data Science, Data Analysis, Machine Learning (Man-made consciousness), Python, Python with Tensorflow, Pandas and more!
&nbsp;
<h2>Course outline</h2>
Learn Data Science and Machine Learning from scratch, get recruited, and have a great time along the way. We are confident that this is the most complete, current and exceptional course you will track down on Data Science and Machine Learning (strong articulation, we know). Completely refreshed for 2023, we utilize the most recent version of Python, Tensorflow 2.0, and all the most recent industry skills and patterns!
<h2>WHAT YOU'LL LEARN</h2>
<ul>
<li>&nbsp;Deep Learning, Transfer Learning and Neural Networks utilizing the most recent Tensorflow 2.0</li>
<li>&nbsp;Present Data Science projects to the executives and partners</li>
<li>&nbsp;Real life contextual analyses and projects to understand how things are done in reality</li>
<li>&nbsp;Execute Machine Learning calculations</li>
<li>&nbsp;Step by step instructions to further develop your Machine Learning models</li>
<li>&nbsp;Fabricate a portfolio of work to have on your resume</li>
<li>&nbsp;Supervised and Unsupervised Learning</li>
<li>&nbsp;Investigate enormous datasets utilizing data visualization apparatuses like Matplotlib and Seaborn</li>
<li>&nbsp;Learn NumPy and the way things are utilized in Machine Learning</li>
<li>&nbsp;Learn to utilize the famous library Scikit-learn in your projects</li>
<li>&nbsp;Ace Machine Learning and how use it on the job</li>
<li>&nbsp;Utilize present day apparatuses that enormous tech organizations like Google, Apple, Amazon and Facebook use</li>
<li>&nbsp;Learn which Machine Learning model to decide for each sort of issue</li>
<li>&nbsp;Learn best practices with regards to Data Science work process</li>
<li>&nbsp;Learn how to program in Python utilizing the most recent Python 3</li>
<li>&nbsp;Learn to pre-process data, clean data, and examine enormous data</li>
<li>&nbsp;Engineer Environment arrangement for Data Science and Machine Learning</li>
<li>&nbsp;Machine Learning on Time Series data</li>
<li>&nbsp;Investigate enormous datasets and fight data utilizing Pandas</li>
<li>&nbsp;A portfolio of Data Science and Machine Learning projects to go after positions in the industry with all code and notebooks gave</li>
<li>&nbsp;Learn about Data Designing and how apparatuses like Hadoop, Spark, and Kafka are utilized in the industry</li>
<li>&nbsp;Learn how to apply Transfer Learning</li>
<li>&nbsp;Learn to perform Classification and Regression modeling</li>
</ul>
&nbsp;
Machine Learning has applications in pretty much every industry and is turning out to be all the more generally utilized each and every year.
<ul>
<li>Advertising</li>
<li>Finance</li>
<li>Medical care and Patient Analysis</li>
<li>Online protection</li>
<li>Retail</li>
<li>Transportation and Strategies</li>
<li>Agribusiness</li>
<li>Web of Things</li>
<li>Gaming and Amusement</li>
<li>Misrepresentation Detection</li>
<li>Irregularity Detection in Assembling</li>
<li>Government</li>
<li>The scholarly world/Exploration</li>
<li>Recommendation Frameworks</li>
<li>Sports (each knew about Moneyball?!)</li>
</ul>
And so many more. It's all over. The skills you'll learn in this course can be applied to these ventures and provide you with a great deal of options for your career.
Alumni of Zero To Dominance are currently working at Google, Tesla, Amazon, Apple, IBM, Uber, Facebook, Shopify + other top tech organizations.
They are likewise functioning as top consultants getting compensated while working from a distance all over the planet.
This can be you.
By selecting today, you'll likewise get to join our elite live online community classroom to learn alongside thousands of students, graduated class, tutors, TAs and Teachers.
Above all, you will learn data science and machine learning from industry experts that have genuine real-world experience having worked for top organizations in Silicon Valley, Toronto and Australia.
This course is centered around productivity with the goal that you never need to squander your energy on confusing, obsolete or inadequate Machine Learning instructional exercises any longer.
This exhaustive and project-based course will acquaint you with each of the cutting edge skills of a Data Scientist and along the way, you will construct some real-world projects to add to your portfolio.
You will likewise gain admittance to all the code, exercise manuals and formats (Jupyter Notebooks) on Github, so you can put them on your portfolio immediately!
This course tackles the greatest test to entering the Data Science and Machine Learning field:
Having every one of the important assets in one spot and learning the most recent patterns and on the job skills that businesses are really searching for.
The curriculum is exceptionally hands-on as we walk you beginning to end of turning into a professional Machine Learning Specialist or Data Scientist.
The course covers 2 tracks:
1️⃣ Developer: Assuming you definitely know programming, you can make a plunge and skirt the section where we show you Python from scratch.
2️⃣ No Programming Experience: On the off chance that you're a finished fledgling, no reason to stress. We take you from the earliest reference point and show you Python from scratch and how to involve it in our real world projects.
Don't stress, you will likewise be going far past the essentials.
Once we ensure you realize the essentials like Machine Learning 101 and Python, we jump deep into advanced topics like Neural Networks, Deep Learning and Transfer Learning so you can get real-life practice and be prepared for the real world.
You will get experience with undeniable Data Science and Machine Learning projects and admittance to bonus programming assets and cheatsheets.
The topics you'll learn in this Data Science and Machine Learning Bootcamp are:
<ul>
<li>Data Exploration and Visualizations</li>
<li>Neural Networks and Deep Learning</li>
<li>Model Evaluation and Analysis</li>
<li>Python 3</li>
<li>Tensorflow 2.0</li>
<li>Numpy</li>
<li>Scikit-Learn</li>
<li>Data Science and Machine Learning Projects and Work processes</li>
<li>Data Visualization in Python with MatPlotLib and Seaborn</li>
<li>Transfer Learning</li>
<li>Image Recognition and Classification</li>
<li>Train/Test and Cross Validation</li>
<li>Supervised Learning: Classification, Regression and Time Series</li>
<li>Decision Trees and Random Timberlands</li>
<li>Ensemble Learning</li>
<li>Hyperparameter Tuning</li>
<li>Utilizing Pandas Data Casings to address complex errands</li>
<li>Use Pandas to handle CSV Records</li>
<li>Deep Learning/Neural Networks with TensorFlow 2.0 and Keras</li>
<li>Utilizing Kaggle and entering Machine Learning competitions</li>
<li>Step by step instructions to introduce your discoveries and intrigue your chief</li>
<li>Step by step instructions to clean and set up your data for analysis</li>
<li>K Closest Neighbors</li>
<li>Support Vector Machines</li>
<li>Regression analysis (Straight Regression/Polynomial Regression)</li>
<li>How Hadoop, Apache Spark, Kafka, and Apache Flink are utilized</li>
<li>Setting up your environment with Conda, MiniConda, and Jupyter Notebooks</li>
<li>Utilizing GPUs with Google Colab</li>
<li>and more!</li>
</ul>
Toward the finish of this course, you will be a finished Data Scientist that can get employed at any organization you can envision.
You will utilize all that you learn in this course to construct professional real-world projects like a Coronary illness Detection Application, Tractor Value Indicator, Canine Variety Image Classifier, and some more.
By and by, you will have a pile of projects you have fabricated that you can flaunt to other people.
What's the primary concern?
Here is reality: most courses show you Data Science and that is all there is to it.
They tell you the best way to get everything rolling, however at that point you don't know where to go from there or how to assemble your own projects.
Or on the other hand, they'll show you a ton of code and complex math on the screen however they don't really make sense of things alright for you to go off on your own and tackle real-life machine learning problems.
Whether you are new to programming, need to step up your Data Science skills, or are coming from an alternate industry, this course is for you.
This course isn't tied in with making you simply code along without understanding the standards so that when you are done with the course you don't understand what to do other than watch another instructional exercise. No!
This course will push you and challenge you to go from a flat out amateur without any Data Science experience, to someone that can go off, disregard Daniel and Andrei, and fabricate their own Data Science and Machine learning work processes, and get recruited 💪.
And you might as well go for broke. You can begin learning at present and in the event that this course isn't all that you expected, we'll discount you 100 percent in 30 days or less. No issues and no questions inquired.
Useful links:
<ol>
<li><a href="https://www.python.org/" target="_new">Python</a></li>
<li><a href="https://www.tensorflow.org/" target="_new">Tensorflow</a></li>
<li><a href="https://pandas.pydata.org/" target="_new">Pandas</a></li>
<li><a href="https://scikit-learn.org/" target="_new">Scikit-learn</a></li>
<li><a href="https://matplotlib.org/" target="_new">Matplotlib</a></li>
<li><a href="https://seaborn.pydata.org/" target="_new">Seaborn</a></li>
<li><a href="https://www.kaggle.com/" target="_new">Kaggle</a></li>
<li><a href="https://docs.conda.io/" target="_new">Conda</a></li>
<li><a href="https://jupyter.org/" target="_new">Jupyter Notebooks</a></li>
<li><a href="https://keras.io/" target="_new">Deep Learning with Keras</a></li>
</ol>

Machine Learning & Data Science 🔥

Complete Machine Learning and Data Science Bootcamp

Elevate your design process with Design Systems with Storybook, v2 workshop by FrontendMasters. Learn documentation, deployment, and collaboration skills, master Storybook's features, and build robust design systems. Perfect for frontend developers, UI/UX designers, and team leads
<h2>Key Takeaways</h2>
By participating&nbsp;along&nbsp;with us in the workshop, you'll learn:
<ul>
<li>Skills in documentation, deployment, and team collaboration</li>
<li>Deep understanding of Storybook&rsquo;s new features and capabilities</li>
<li>Mastery in creating and managing a robust design system</li>
<li>Techniques for building atomic, responsive, and accessible components</li>
<li>Best practices in implementing visual regression testing and dark mode</li>
</ul>
<h3>Is This Workshop for Me?</h3>
Frontend developers, UI/UX designers, and team leads looking to leverage Storybook for creating and scaling design systems. The workshop is mostly framework-agnostic but uses React for demonstrations.
&nbsp;
<h2>Workshop Details</h2>
This workshop offers a comprehensive guide to building design systems using Storybook. Covering everything from basic setup to advanced features, attendees will learn about atomic design, accessibility, visual regression testing, responsive design, and dark mode implementation. The workshop emphasizes practical, hands-on learning for effective team collaboration and documentation.
<h3>Any Prerequisites?</h3>
<ul>
<li>Basic knowledge of JavaScript and familiarity with React</li>
<li>Understanding of CSS and styling concepts</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 17, 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>
<h2>Daily Schedule</h2>
<ul>
<li>9:30AM</li>
<li>Introduction to Design Systems and Storybook</li>
<li>10:00AM</li>
<li>Setting Up Storybook in Your Project</li>
<li>10:30AM</li>
<li>Utilizing Design Tokens and Theming in Storybook</li>
<li>11:00AM</li>
<li>Building Atomic Components with Enhanced UI Controls</li>
<li>11:30AM</li>
<li>Managing Component States and Variants in Storybook</li>
<li>12:00PM</li>
<li>Lunch Break</li>
<li>1:00PM</li>
<li>Auditing Accessibility in Components</li>
<li>1:30PM</li>
<li>Implementing Visual Regression Testing</li>
<li>2:00PM</li>
<li>Leveraging Enhanced Documentation Features</li>
<li>2:30PM</li>
<li>Exploring Advanced Addons and Integrations</li>
<li>3:00PM</li>
<li>Strategies for Responsive Design and Dark Mode Implementation</li>
<li>3:30PM</li>
<li>Automating Deployment and Maintaining the Design System</li>
<li>4:00PM</li>
<li>Collaborative Techniques and Workflow Improvements</li>
<li>4:30PM</li>
<li>Strategies for Scaling Your Design System</li>
</ul>
&nbsp;

Design Systems with Storybook 🔥

Design Systems with Storybook, v2 [FrontendMasters]

Design Systems with Storybook, v2 [FrontendMasters]

Key Takeaways

Is This Workshop for Me?

Workshop Details

Any Prerequisites?

Event Details

What

When

Where

Daily Schedule

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

Design Systems with Storybook, v2 [FrontendMasters]

Key Takeaways

Is This Workshop for Me?

Workshop Details

Any Prerequisites?

Event Details

What

When

Where

Daily Schedule

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 👇 )