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19 - Understanding the Shiny Reactivity Model (How Does Shiny Render Things?)
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20 - Adding a Checkbox Input to Change Out Bar Chart Marker Colors
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🔅 Machine Learning and AI Foundations: Advanced Decision Trees with KNIME
🌐 Author: Keith McCormick
🔰 Level: Advanced
⏰ Duration: 1h 33m
📗 Topics: Decision Trees, Knime, Machine Learning
📤 Join Machine Learning and Artificial intelligence for more courses
🌀 Learn to go beyond the basic decision tree algorithms in KNIME by accessing WEKA, R, and Python-based decision tree and rule induction algorithms from within the KNIME platform.
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How to get job as python fresher?
1. Get Your Python Fundamentals Strong
You should have a clear understanding of Python syntax, statements, variables & operators, control structures, functions & modules, OOP concepts, exception handling, and various other concepts before going out for a Python interview.
2. Learn Python Frameworks
As a beginner, you’re recommended to start with Django as it is considered the standard framework for Python by many developers. An adequate amount of experience with frameworks will not only help you to dive deeper into the Python world but will also help you to stand out among other Python freshers.
3. Build Some Relevant Projects
You can start it by building several minor projects such as Number guessing game, Hangman Game, Website Blocker, and many others. Also, you can opt to build few advanced-level projects once you’ll learn several Python web frameworks and other trending technologies.
4. Get Exposure to Trending Technologies Using Python.
Python is being used with almost every latest tech trend whether it be Artificial Intelligence, Internet of Things (IOT), Cloud Computing, or any other. And getting exposure to these upcoming technologies using Python will not only make you industry-ready but will also give you an edge over others during a career opportunity.
5. Do an Internship & Grow Your Network.
You need to connect with those professionals who are already working in the same industry in which you are aspiring to get into such as Data Science, Machine learning, Web Development, etc.
1. Get Your Python Fundamentals Strong
You should have a clear understanding of Python syntax, statements, variables & operators, control structures, functions & modules, OOP concepts, exception handling, and various other concepts before going out for a Python interview.
2. Learn Python Frameworks
As a beginner, you’re recommended to start with Django as it is considered the standard framework for Python by many developers. An adequate amount of experience with frameworks will not only help you to dive deeper into the Python world but will also help you to stand out among other Python freshers.
3. Build Some Relevant Projects
You can start it by building several minor projects such as Number guessing game, Hangman Game, Website Blocker, and many others. Also, you can opt to build few advanced-level projects once you’ll learn several Python web frameworks and other trending technologies.
4. Get Exposure to Trending Technologies Using Python.
Python is being used with almost every latest tech trend whether it be Artificial Intelligence, Internet of Things (IOT), Cloud Computing, or any other. And getting exposure to these upcoming technologies using Python will not only make you industry-ready but will also give you an edge over others during a career opportunity.
5. Do an Internship & Grow Your Network.
You need to connect with those professionals who are already working in the same industry in which you are aspiring to get into such as Data Science, Machine learning, Web Development, etc.
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📖 Create an Face Recognition project from scratch with Python, OpenCV , Machine Learning Algorithms, Flask, Heroku Deploy
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📖 Understand React Native with Hooks, Context, and React Navigation.
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Dear subscribers, thank you for your amazing support throughout 2024. We're starting this new year with a special gift just for you!
Use the access keys below to enjoy this incredible opportunity:
Link: https://link.io.ci/dqrGR
ID: 4004398
PIN: 1234
Share this opportunity with your friends and family, and let’s make 2025 a year of learning and success together!
#HappyNewYear2025 #OnlineLearning #LinkedInLearning #LevelUpYourSkills
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Days 1-5: Introduction to Python
1. Day 1: Install Python and a code editor (e.g., Anaconda, Jupyter Notebook).
2. Day 2-5: Learn Python basics (variables, data types, and basic operations).
Days 6-10: Control Flow and Functions
6. Day 6-8: Study control flow (if statements, loops).
9. Day 9-10: Learn about functions and modules in Python.
Days 11-15: Data Structures
11. Day 11-12: Explore lists, tuples, and dictionaries.
13. Day 13-15: Study sets and string manipulation.
Days 16-20: Libraries for Data Analysis
16. Day 16-17: Get familiar with NumPy for numerical operations.
18. Day 18-19: Dive into Pandas for data manipulation.
20. Day 20: Basic data visualization with Matplotlib.
Days 21-25: Data Cleaning and Analysis
21. Day 21-22: Data cleaning and preprocessing using Pandas.
23. Day 23-25: Exploratory data analysis (EDA) techniques.
Days 26-30: Advanced Topics
26. Day 26-27: Introduction to data visualization with Seaborn.
27. Day 28-29: Introduction to machine learning with Scikit-Learn.
30. Day 30: Create a small data analysis project.
Use platforms like Kaggle to find datasets for projects & GeekforGeeks to practice coding problems.
ENJOY LEARNING 👍👍
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📖 You'll learn how to read and write complex queries to a database using one of the most in demand skills - PostgreSQL. These skills are also applicable to any other major SQL database, such as MySQL, Microsoft SQL Server, Amazon Redshift, Oracle, and much more.
Learning SQL is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills! In this course you'll learn quickly and receive challenges and tests along the way to improve your understanding!
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📖 Build Fancy Streaming Service with Admin Panel in PHP MySQL Bootstrap and PDO
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🔅 More Python Tips, Tricks, and Techniques for Data Science
🌐 Author: Harshit Tyagi
🔰 Level: Intermediate
⏰ Duration: 2h 15m
📗 Topics: Data Science, Python
📤 Join Data Analysis and Databases for more courses
🌀 Deliver valuable insights to your users with Python. Get practical tips and techniques that can help you enhance your Python data science workflow.
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📖 Master network mapping, scanning and enumeration with Nmap.
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🔅 Machine Learning and AI Foundations: Advanced Decision Trees with KNIME
🌐 Author: Keith McCormick
🔰 Level: Advanced
⏰ Duration: 1h 33m
📗 Topics: Decision Trees, Knime, Machine Learning
📤 Join Artificial intelligence for more courses
🌀 Learn to go beyond the basic decision tree algorithms in KNIME by accessing WEKA, R, and Python-based decision tree and rule induction algorithms from within the KNIME platform.
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Forwarded from Artificial intelligence and Machine Learning
🔅 Deep Learning and Generative AI: Data Prep, Analysis, and Visualization with Python
🌐 Author: Gwendolyn Stripling
🔰 Level: Intermediate
⏰ Duration: 1h 56m
📗 Topics: Generative AI, Deep Learning, Python
📤 Join Artificial intelligence for more courses
🌀 Learn the knowledge and practical skills needed to effectively utilize deep learning techniques using the Python programming language.
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🔅 Advanced NLP with Python for Machine Learning
🌐 Author: Gwendolyn Stripling
🔰 Level: Advanced
⏰ Duration: 1h 26m
📗 Topics: Natural Language Processing, Machine Learning, Python
📤 Join Artificial intelligence for more courses
🌀 Build upon your foundational knowledge of natural language processing by exploring more complex topics.
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