Convolutional Neural Networks (CNNs) with Python & TensorFlow - A Comprehensive Guide
Channel: Codanics
Date: 2023-06-06

#datascience 
---------------------------------------------------------------------------------------------------------------------------------------
Video Description:

--------Unleash the power of Convolutional Neural Networks (CNNs) with this in-depth tutorial! We'll be using Python and TensorFlow to dive into the world of deep learning and artificial intelligence.

In this video, you'll learn how to code a Convolutional Neural Network from scratch. We’ll start with the basics - what CNNs are and how they work. We'll then take a deep dive into how to implement these powerful networks using Python, TensorFlow - one of the most popular deep learning libraries out there.

Key Points Covered:
Introduction
Basics of Convolutional Neural Networks
Why Use CNNs?
Python and TensorFlow Installation
CNN Coding Session: Setup and Data Preparation
CNN Coding Session: Model Building
CNN Coding Session: Training and Evaluation
Practical CNN Applications
Tips and Tricks for Effective CNN Implementation
Conclusion

By the end of this tutorial, you'll have the knowledge and skills to apply CNNs to real-world problems, taking your data analysis and machine learning projects to the next level. Whether you're a novice programmer or an experienced data scientist, this video will provide valuable insights into the world of Convolutional Neural Networks.

Remember to like, share, and subscribe to our channel for more comprehensive coding tutorials and deep learning content.

#ConvolutionalNeuralNetworks #CNN #Python #TensorFlow #DeepLearning #ArtificialIntelligence #CodingTutorial"-------------------------------------------------------------------------------------------------------------------------------

✅Subscribe to our Channel to learn more about the top Data Science, Machine Learning and Deep Learning :  https://www.youtube.com/c/Codanics

---------------------------------------------------------------------------------------------------------------------------------------




---------------------------------------------------------------------------------------------------------------------------------------
Explore other free courses here:
🔥  Python ka chilla v1.0 for Data Science (playlist): https://youtube.com/playlist?list=PL9XvIvvVL50HVsu-Ao8NBr0UJSO8O6lBI

🔥  Machine learning ka chilla (playlist): https://www.youtube.com/watch?v=KYl9zmSt-Ik&list=PL9XvIvvVL50HHzaLPtFBOuikAWa0JdhMW

🔥 Streamlit course for dash boards and webapps for data science (playlist): 
https://youtube.com/playlist?list=PL9XvIvvVL50FG8TUsLScsLMmJDacK36x2

🔥  Cloud computing (playlist): https://youtube.com/playlist?list=PL9XvIvvVL50H72Q75WkYA_2zjZok30Rvp

🔥  #RwithAammar Programming with R for Data Analysis and Data Science (Playlist): https://www.youtube.com/playlist?list=PL9XvIvvVL50E8HimtAnVL8N70MqImYOLS

🔥 Make publication ready graphs in Rstudio: https://www.youtube.com/playlist?list=PL9XvIvvVL50Hi2RGu-zlNEnk9WJMjPH-g

🔥 Computer Vision openCV in Python (Playlist): https://youtube.com/playlist?list=PL9XvIvvVL50GKoKrluZ1A96Bsuw8qC-3r

🔥MS Excel for Data Analysis: https://www.youtube.com/playlist?list=PL9XvIvvVL50Hl4kVygAWYEpBXUteQlAiN

🔥 SQL complete course in Hindi/Urdu: https://youtube.com/playlist?list=PL9XvIvvVL50FszjOhcZw9WXIJQY6ZwV5g

---------------------------------------------------------------------------------------------------------------------------------------
🔥-Follow me on following platforms:
1. Twitter: https://twitter.com/aammar_tufail
2. github: https://github.com/AammarTufail
3. Tiktok:  https://www.tiktok.com/@draammar
---------------------------------------------------------------------------------------------------------------------------------------
#dataScience
Join this telegram group for regular updates via zoom meeting 1-to-1 sessions: https://t.me/codanics
---------------------------------------------------------------------------------------------------------------------------------------

for more details:
www.codanics.com