Complete Machine Learning & Data Science with Python | A-Z
Complete Machine Learning & Data Science with Python | A-Z
Use Scikit, learn NumPy, Pandas, Matplotlib, Seaborn and dive into machine learning A-Z with Python and Data Science.
Sure! "Complete Machine Learning & Data Science with Python | A-Z" is a course on Udemy that teaches you how to use Scikit, learn NumPy, Pandas, Matplotlib, Seaborn, and dive into machine learning A-Z with Python and Data Science¹. The course has been designed by a Data Scientist and a Machine Learning expert so that they can share their knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way³. It has over 900,000 students worldwide who trust this course³.
The course covers topics such as:
- Data Preprocessing
- Regression
- Classification
- Clustering
- Association Rule Learning
- Reinforcement Learning
- Natural Language Processing
- Deep Learning
You can check out the course on Udemy's website¹ if you're interested in learning more about it.
I hope this helps! Let me know if you have any other questions.
Source: Conversation with Bing, 5/15/2023
(1) Complete Machine Learning & Data Science with Python | A-Z.
(2) Machine Learning A-Z (Python & R in Data Science Course).
(3) Complete Machine Learning & Data Science with Python| ML A-Z.
What you'll 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
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