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47 - Final words! Like & Subscribe pretty please!!
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11 - Getting Started with Code (Part 2)
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12 - Adding Shiny Components (Inputs, Outputs, & Display Messages)
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13 - Creating an Additional Visualization (Sales Over Time by City)
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14 - What are Reactive.Calcs and How Do We Use Them Properly? (DataFrame Best Practices)
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15 - Creating an Additional Visualization (Sales Over Time by City) — Continued
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16 - Filtering City Data with Select Inputs (UI.Input_Selectize)
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17 - Rendering Shiny Inputs Within Text
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18 - Quick Formatting Adjustments
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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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