Data Science and Analytics, Machine Learning, Deep Learning and Computer Vision so on!

Repository of notebooks of use-cases I worked on during my Cainvas internship at AI Technology and Systems.

Computer Vision Course Notebooks, 2022

Notebooks from advanced CV courses

Jupyter notebooks for predicting tides, using unsupervised neural net clustering.

This repository consist of various notebooks related to Deep Learning Processes

This repository consists of deep learning and it's related notebooks

Collection of Machine Learning Python/Jupyter Notebook Files (Classical ML & Deep Learning)

Notebook para demonstrar como utilizar a API Keras para visualizar as ativações de uma CNN.

Google colab notebook for the Kaggle MINST cnn submission / Saved model used in the demo

My notebook on Neural Networks comprising of ANN, CNN, LSTM using keras.

The notebook is about improvement of classification accuracy for hard items in FashionMNIST dataset using random erase for regularization.

This is a very brief notebook on NLP, it contains a "Disaster Analysis" project in which all the possible architectures were shown and described briefly.

This notebook demonstrates data augmentation as showcased by Tensorflow: a technique to increase the diversity of your training set by applying random (but realistic) transformations, such as image rotation.

This is a binary sentiment classifier for the IMDB movie dataset using traditional machine learning and deep learning algorithms. The code is written in Python and executed on Jupyter Notebook.

Welcome to "CNN-Deep-Learning-in-Nutshell" repository! Collection of Jupyter notebooks is designed to comprehensive resource for diving into the exciting world of Convolutional Neural Networks (CNNs) and exploring various other deep learning topics.

Developed multiple Deep Learning projects using CNN, RNN, ANN, and fine-tuned models to tackle real-world challenges. Optimized architectures for diverse tasks, ensuring high accuracy and efficiency. Shared Jupyter Notebooks, providing insights into the model-building process to assist others in utilizing my work.

This project is one of the tasks I got during college. In this project, I used the python programming language and created it in a Jupyter Notebook. In this project, I use OpenCV, TensorFlow, Keras, Mobilenet V2, Haarcascade, and datasets. For the dataset I got it in Kaggle and trained the data through Google Colab.

A small collection of my Miscellaneous notebooks and scripts.