Learning concept is one thing but to know how to apply them is another. While learning theoretical concepts most of us lack practical knowledge since it's hard to apply them simultaneously and write codes.

But Thanks to Michael Kroeker and Deep Learning Studio by Deep Cognition which always helped me to solve many problem easily and in less than no time

Now I can learn concepts and apply them simultaneously by a newly launched course on Udemy that will help you build neural networks in seconds.

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Here you'll learn

-How To Build Deep Neural Networks In Seconds Using Deep Learning Studio.
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-How To Understand Neural Networks Without Math Formulas.
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-Understand Normalization,Dropout Without Heavy Math Or Complicated Technical Explanations.
and more...

#machinelearning #deeplearning #programming #learning

🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

Data science is not about memorization, it's about making connections and applying your knowledge.

If you can understand a lot of different materials and subjects and see how they connect, then you'll naturally remember these subjects better. This is simply how the brain is structured - everything is connected to something else.

➡️ More connections = more retention.

Connect new information with long-term memories and then reinforce those connections to create new long-term memories.

And begin to apply your knowledge to create something new and you will not only increase your understanding of the subject, but you'll increase your retention as well because the information will have context.

Ironically, this approach is much more effective than *trying* to memorize material.

👉 So if you're ever wondering "should I memorize this," just reframe your perspective to ask:

• how does this information relate to what I already know?
• how can I apply this to a problem I'm facing?
• what can I create with this new knowledge?
• who can I teach this new subject to?

and the ability to remember what you've learned will take care of itself.

#datascience #learning

✴️ @AI_Python_EN

Machine Learning Cheat Sheet #Learning #MachineLearning

✴️ @AI_Python_EN

#imbalancedData
What is it?
Ans-> Suppose, you are having a Classification problem with 2M records. The Output variable is having 2 categories (Yes- 500, No- 1.99M or more).

This is the imbalanced data, as one category is far less than the other category in the Output variable.

Examples-> Credit Card fraud, Cancer Detection(or any other disease that is severe), and many more.

How to deal with it?
1) Undersampling
2) Oversampling

#datascience #dataanalysis #learning

✴️ @AI_Python_EN

Welcome to @ai_machinelearning_big_data the world of :
* #Artificial #Intelligence,
* #Deep #Learning,
* #Machine #Learning,
* #Data #Science
* #Python Programming language
* and more advanced research
links🔗 and more you wanted.
Join us and learn hot topics of Computer Science together.👇👇👇

@ai_machinelearning_big_data