Machine Learning & Data Science with Python & Kaggle | A-Z

Machine Learning A-Z course from zero with Python, Kaggle, Pandas and Numpy for data analysis with hands-on examples

Created by: Oak Academy
AI, Comptia, Cybersecurity, Android, Development & IT course

Created by: OAK Academy Team
instructor

Created by: Ali̇ CAVDAR
DATA SCIENTIST AND IT INSTRUCTOR

What Will I Learn?

• Machine learning isn’t just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries.
• Learn Machine Learning with Hands-On Examples
• What is Machine Learning?
• Machine Learning Terminology
• Evaluation Metrics
• What are Classification vs Regression?
• Evaluating Performance-Classification Error Metrics
• Evaluating Performance-Regression Error Metrics
• Supervised Learning
• Cross Validation and Bias Variance Trade-Off
• Use matplotlib and seaborn for data visualizations
• Machine Learning with SciKit Learn
• Linear Regression Algorithm
• Logistic Regresion Algorithm
• K Nearest Neighbors Algorithm
• Decision Trees And Random Forest Algorithm
• Support Vector Machine Algorithm
• Unsupervised Learning
• K Means Clustering Algorithm
• Hierarchical Clustering Algorithm
• Principal Component Analysis (PCA)
• Recommender System Algorithm
• Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective.
• Python is a general-purpose, object-oriented, high-level programming language.
• Python is a multi-paradigm language, which means that it supports many programming approaches. Along with procedural and functional programming styles
• Python is a widely used, general-purpose programming language, but it has some limitations. Because Python is an interpreted, dynamically typed language
• Python is a general programming language used widely across many industries and platforms. One common use of Python is scripting, which means automating tasks.
• Python is a popular language that is used across many industries and in many programming disciplines. DevOps engineers use Python to script website.
• Python has a simple syntax that makes it an excellent programming language for a beginner to learn. To learn Python on your own, you first must become familiar
• Machine learning describes systems that make predictions using a model trained on real-world data.
• Machine learning is being applied to virtually every field today. That includes medical diagnoses, facial recognition, weather forecasts, image processing.
• It's possible to use machine learning without coding, but building new systems generally requires code.
• Python is the most used language in machine learning. Engineers writing machine learning systems often use Jupyter Notebooks and Python together.
• Machine learning is generally divided between supervised machine learning and unsupervised machine learning. In supervised machine learning.
• Machine learning is one of the fastest-growing and popular computer science careers today. Constantly growing and evolving.
• Machine learning is a smaller subset of the broader spectrum of artificial intelligence. While artificial intelligence describes any "intelligent machine"
• A machine learning engineer will need to be an extremely competent programmer with in-depth knowledge of computer science, mathematics, data science.
• Python machine learning, complete machine learning, machine learning a-z

Requirements

• Basic knowledge of Python Programming Language
• Be Able To Operate & Install Software On A Computer
• Free software and tools used during the machine learning a-z course
• Determination to learn machine learning and patience.
• Motivation to learn the the second largest number of job postings relative program language among all others
• Data visualization libraries in python such as seaborn, matplotlib
• Curiosity for machine learning python
• Desire to learn Python
• Desire to learn matplotlib
• Desire to learn pandas and numpy
• Desire to learn machine learning a-z, complete machine learning
• Any device you can watch the course, such as a mobile phone, computer or tablet.
• Watching the lecture videos completely, to the end and in order.
• Nothing else! It’s just you, your computer and your ambition to get started today.
• LIFETIME ACCESS, course updates, new content, anytime, anywhere, on any device.

Target audience

• Anyone who wants to start learning "Machine Learning"
• Anyone who needs a complete guide on how to start and continue their career with machine learning
• Students Interested in Beginning Data Science Applications in Python Environment
• People Wanting to Specialize in Anaconda Python Environment for Data Science and Scientific Computing
• Students Wanting to Learn the Application of Supervised Learning (Classification) on Real Data Using Python
• Anyone eager to learn python for data science and machine learning bootcamp with no coding background
• Anyone who plans a career in data scientist,
• Software developer whom want to learn python,
• Anyone interested in machine learning a-z
• People who want to become data scientist
• Poeple who want tp learn complete machine learning