Deep Learning Tutorial 4 - Cats vs Dogs Classification using CNN & Image Augmentation
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Title: Cats and Dogs Classification
Title: Cats and Dogs Classification with CNN & Image Augmentation | Improve Accuracy
Description:
🐱🐶 Welcome to our comprehensive lecture on Cats and Dogs Classification using Convolutional Neural Networks (CNNs) and Image Augmentation for enhanced accuracy! In this video, we dive deep into the world of deep learning and computer vision to help you understand and implement a powerful CNN model for a classic image classification problem.
💬 If you have any questions or suggestions, please leave a comment below. We're here to help and we appreciate your feedback! Happy learning! 🚀
#CatsAndDogs #CNN #ImageClassification #DeepLearning #ImageAugmentation #ComputerVision
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Description:
🐱🐶 Welcome to our comprehensive lecture on Cats and Dogs Classification using Convolutional Neural Networks (CNNs) and Image Augmentation for enhanced accuracy! In this video, we dive deep into the world of deep learning and computer vision to help you understand and implement a powerful CNN model for a classic image classification problem.
💬 If you have any questions or suggestions, please leave a comment below. We're here to help and we appreciate your feedback! Happy learning! 🚀
#CatsAndDogs #CNN #ImageClassification #DeepLearning #ImageAugmentation #ComputerVision
🔊 Watch till last for a detailed description
💯 Read Full Blog with Code
https://kgptalkie.com
https://github.com/laxmimerit/deep-le...
💬 Leave your comments and doubts in the comment section
📌 Save this channel and video for watch later
👍 Like this video to show your support and love ❤️
~~~~~~~~
🆓 Watch My Top Free Data Science Videos
👉🏻 Python for Data Scientist
https://bit.ly/3dETtFb
👉🏻 Machine Learning for Beginners
https://bit.ly/2WOVh7N
👉🏻 Feature Selection in Machine Learning
https://bit.ly/2YW6ZQH
👉🏻 Text Preprocessing and Mining for NLP
https://bit.ly/31sYMUN
👉🏻 Natural Language Processing (NLP)
Tutorials https://bit.ly/3dF1cTL
👉🏻 Deep Learning with TensorFlow 2.0
and Keras https://bit.ly/3dFl09G
👉🏻 COVID 19 Data Analysis and Visualization
Masterclass https://bit.ly/31vNC1U
👉🏻 Machine Learning Model Deployment Using
Flask at AWS https://bit.ly/3b1svaD
👉🏻 Make Your Own Automated Email Marketing
Software in Python https://bit.ly/2QqLaDy
***********
🤝 BE MY FRIEND
🌍 Check Out ML Blogs: https://kgptalkie.com
🐦Add me on Twitter: Twitter: laxmimerit
📄 Follow me on GitHub: https://github.com/laxmimerit
📕 Add me on Facebook: Facebook: kgptalkie
💼 Add me on LinkedIn: LinkedIn: laxmimerit
👉🏻 Complete Udemy Courses: https://bit.ly/32taBK2
⚡ Check out my Recent Videos: https://bit.ly/3ldnbWm
🔔 Subscribe me for Free Videos: https://bit.ly/34wN6T6
🤑 Get in touch for Promotion: [email protected]
✍️🏆🏅🎁🎊🎉✌️👌⭐⭐⭐⭐⭐
ENROLL in My Highest Rated Udemy Courses
to 🔑 Unlock Data Science Interviews 🔎 and Tests
📚 📗 NLP: Natural Language Processing ML Model Deployment at AWS
Build & Deploy ML NLP Models with Real-world use Cases.
Multi-Label & Multi-Class Text Classification using BERT.
Course Link: https://bit.ly/bert_nlp
📊 📈 Data Visualization in Python Masterclass: Beginners to Pro
Visualization in matplotlib, Seaborn, Plotly & Cufflinks,
EDA on Boston Housing, Titanic, IPL, FIFA, Covid-19 Data.
Course Link: https://bit.ly/udemy95off_kgptalkie
📘 📙 Natural Language Processing (NLP) in Python for Beginners
NLP: Complete Text Processing with Spacy, NLTK, Scikit-Learn,
Deep Learning, word2vec, GloVe, BERT, RoBERTa, DistilBERT
Course Link: https://bit.ly/intro_nlp
📈 📘 2021 Python for Linear Regression in Machine Learning
Linear & Non-Linear Regression, Lasso & Ridge Regression, SHAP, LIME, Yellowbrick, Feature Selection & Outliers Removal. You will learn how to build a Linear Regression model from scratch.
Course Link: https://bit.ly/regression-python
📙📊 2021 R 4.0 Programming for Data Science || Beginners to Pro
Learn Latest R 4.x Programming. You Will Learn List, DataFrame, Vectors, Matrix, DateTime, DataFrames in R, GGPlot2, Tidyverse, Machine Learning, Deep Learning, NLP, and much more.
Course Link: http://bit.ly/r4-ml
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