Deep Learning Prerequisites: The Numpy Stack in Python (V2 +) is a training package for deep learning prerequisites in the Python programming language. These prerequisites include the Numpy, Scipy, Pandas, and Matplotlib modules, all of which will teach you all of them and prepare you for the development of in-depth machine learning and artificial intelligence. Many people today want to learn these concepts and technologies, but many of them refuse to continue because they are not familiar with the necessary modules. One of these modules is called Numpy. This module is the basis of everything else and is used to build arrays that are designed to change and speed, so they can also be used to build operational matrices such as multiplication and subtraction.
The next module is called Pandas. This library is designed to build a DataFrame (similar to the R language), which is very useful for processing and managing large amounts of information. With the help of this module, tasks such as filtering, applying functions and combinations are easily done. Matplotlib module is used to draw various graphs such as linear and histograms and Scipy module is also used to calculate statistical specifications. With this module you can calculate values such as PDF and CDF, sample a distribution and perform statistical tests. In general, if you want to enter the world of deep learning and artificial intelligence, mastering these modules is vital that this training package will provide you with the commands, applications, functions and everything that these modules have to offer. teaches .
What do you learn:
- Supervised machine learning such as categorization and regression using real-world examples and Scikit-Learn
- How to use Numpy, Scipy, Matplotlib and Pandas to implement numerical algorithms
- How to implement Stack in Numpy
- Learn the differences and strengths of different machine learning models
- And …
This training is suitable for people who:
- Inexperienced or inexperienced people about Numpy who want to learn deep and machine learning later
- People who have previously tried machine learning or data science but have not been successful
Profile of Deep Learning Prerequisites: The Numpy Stack in Python (V2 +):
- Publisher: Udemy
- Instructor: Lazy Programmer Inc
- English language
- Level of training: from basic to advanced
- Number of courses: 50
- Duration: 5 hours and 54 minutes
- Understand linear algebra and the Gaussian distribution
- Be comfortable with coding in Python
- You should already know “why” things like a dot product, matrix inversion, and Gaussian probability distributions are useful and what they can be used for
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Version 2020/11 has increased by at least 3 lessons and about half an hour compared to 2020/5.