Description
Machine Learning and Data Science Course with Python, Kaggle and Pandas. Machine Learning and Data Science Course with Python, Kaggle and Pandas. Hello, welcome to the training course “Machine Learning and Data Science with Python, Kaggle and Pandas”. AZ Machine Learning Course with Python, Kaggle, Pandas and Numpy for data analysis with practical examples. Machine learning is a branch of artificial intelligence (AI) and computer science that focuses on using data and algorithms to mimic the way humans learn and gradually improve its accuracy. You can develop the basic skills needed to build neural networks and progress to creating more complex functions through the Python and R programming languages. Machine learning helps you stay ahead of new trends, technologies and applications. Today machine learning is used in almost every field. This includes medical diagnosis, facial recognition, weather forecasting, image processing and much more. In any situation where pattern recognition, prediction and analysis are important, machine learning can be useful. Machine learning is often a disruptive technology when applied to new industries and fields. Machine learning engineers can find new ways to apply machine learning techniques to optimize and automate existing processes. With the right data, you can use machine learning techniques to identify very complex patterns and make very accurate predictions. Pandas is an open source Python package commonly used for data science/data analysis and machine learning tasks. Pandas is built on top of another package called Numpy that supports multidimensional arrays. Pandas is a fast, powerful, flexible, and easy-to-use open source data analysis and manipulation tool built on the Python programming language. Numpy is a library for the Python programming language that adds support for large, multidimensional arrays and matrices, along with a large set of high-level math functions to operate on these arrays. Additionally, Numpy forms the foundation of the machine learning stack. We have “Machine Learning and Data Science with Python and Kaggle” for you. We have designed a simple course A-Z for Python programming language and machine learning. In this course, you will get simple explanations with projects. With this course, you will learn machine learning step by step. I made it simple and easy with exercises, challenges, and many real examples. You will also get to know about the Kaggle platform step by step with the Heart Attack Prediction Kaggle project. Kaggle is a platform where data scientists can compete in machine learning challenges. These challenges can be anything from predicting housing prices to identifying cancer cells. Kaggle has a huge community of data scientists who are always ready to help others with data science problems. If you are ready to learn now, enroll in the course “Machine Learning and Data Science with Python, Kaggle, and Pandas”. A-Z Machine Learning course with Python, Kaggle, Pandas, and Numpy for data analysis with practical examples. See you in the course!
What you will learn in Machine Learning and Data Science with Python Kaggle and Pandas course
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Machine learning isn’t just useful for texting or smartphone voice recognition. Machine learning is constantly being applied to new industries.
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Learn Machine Learning with Practical Examples
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What is Machine Learning?
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Machine Learning Terminology
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What is classification vs regression?
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Evaluation of the performance classification error criterion
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Evaluating performance regression error measures
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Cross-validation and trade-off bias variance
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Use matplotlib and seaborn to visualize data
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Machine Learning with SciKit Learn
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Linear Regression Algorithm
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Logistic Regression Algorithm
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K Nearest Neighbors Algorithm
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Decision Tree and Random Forest Algorithms
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Support Vector Machine Algorithms
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K means clustering algorithm
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Hierarchical clustering algorithm
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Principal Component Analysis (PCA)
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Recommender System Algorithms
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OAK Academy’s Python instructors are experts in everything from software development to data analysis and are known for their effectiveness.
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Python is a general-purpose, object-oriented, high-level programming language.
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Python is a multi-paradigm language, meaning it supports multiple programming approaches. Along with procedural and functional programming styles
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Python is a general purpose and widely used programming language, but it has its limitations. Because Python is an interpreted and dynamic language
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Python is a general purpose programming language that is widely used across many industries and platforms. A common use of Python is scripting, which means automating tasks.
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Python is a popular language used in many industries and across many programming disciplines. DevOps engineers use Python to script websites.
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Python has a simple syntax which makes it a great programming language for beginners to learn. To learn Python on your own, you must first become familiar with it
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Machine learning describes systems that make predictions using models trained on real-world data.
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Today machine learning is used in almost every field. This includes medical diagnosis, face recognition, weather forecasting, image processing.
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It is possible to use machine learning without writing code, but building new systems typically requires code.
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Python is the most commonly used language in machine learning. Engineers writing machine learning systems often use Jupyter and Python notebooks together.
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Machine learning is generally divided into supervised machine learning and unsupervised machine learning. In supervised machine learning
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Machine learning is one of the fastest growing and most popular careers in computer science. It is constantly growing and evolving.
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Machine learning is a small subset of the broader spectrum of artificial intelligence. While artificial intelligence describes any “intelligent machine”.
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A machine learning engineer must be a highly skilled programmer with in-depth knowledge of computer science, mathematics, data science.
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Python Machine Learning, Complete Machine Learning, Edge Machine Learning
This course is suitable for those who
- Anyone who wants to start learning “Machine Learning”.
- Anyone who needs a complete guide on how to start and continue working with machine learning
- Students interested in starting data science applications in a Python environment
- People who want to specialize in the Anaconda Python environment for data science and scientific computing
- Students who want to learn the application of supervised learning (classification) on real data using Python
- Anyone interested in learning Python for Data Science and Machine Learning Bootcamp without a coding background
- Anyone considering a career as a data scientist,
- A software developer who wants to learn Python.
- Anyone interested in machine learning
- People who want to become scientists
- People who want to learn complete Machine Learning
Description of Machine Learning and Data Science with Python Kaggle and Pandas course
Course topic Machine Learning and Data Science with Python Kaggle and Pandas 1/2024
Prerequisites of Machine Learning and Data Science with Python Kaggle and Pandas Courses
- Basic knowledge of Python programming language
Be able to run and install software on a computer
Free software and tools used during the Machine Learning Edge course
Determination to learn machine learning and patience.
Motivation to learn program language with second highest number of job postings relative to all others
Data visualization libraries in Python like Seaborn, Matplotlib
Curiosities for Machine Learning Python
I want to learn Python
Desire to learn matplotlib
Desire to learn pandas and numpy
Machine Learning as a Desire to Learn, Complete Machine Learning
You can view the courses on any device, such as a mobile phone, computer or tablet.
Watching the lecture video completely, end-to-end and in sequence.
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.
Machine Learning and Data Science with Python Kaggle and Pandas Courses Images
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