Pinned Repositories
100-pandas-puzzles
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
365-Days-Computer-Vision-Learning-Linkedin-Post
365 Days Computer Vision Learning Linkedin Post
Audio-Visual-Cryptography-using-AES-RSA
AudioSignalProcessingForML
Code and slides of my YouTube series called "Audio Signal Proessing for Machine Learning"
email-form-nodejs
keras-autoencoders
Autoencoders in Keras
meme-gen-task
Papers-Literature-ML-DL-RL-AI
Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
papers-with-annotations
Research papers with annotations, illustrations and explanations
vision
Datasets, Transforms and Models specific to Computer Vision
mahima8178's Repositories
mahima8178/vision
Datasets, Transforms and Models specific to Computer Vision
mahima8178/100-pandas-puzzles
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
mahima8178/365-Days-Computer-Vision-Learning-Linkedin-Post
365 Days Computer Vision Learning Linkedin Post
mahima8178/Audio-Visual-Cryptography-using-AES-RSA
mahima8178/adv_tf
mahima8178/ALL-Cell-Classification
The proposed hybrid convolutional neural network architecture is a neural network architecture consisting of a combination of the VGG16, ResNet50, InceptionV3, and the DenseNet121 architectures, all of which have been pretrained on the ImageNet database. The purpose of this model is to identify if an image of a cell has acute lymphocytic leukemia (also referred to as ALL), or if it is a healthy cell. The dataset used contains 1700 images from the training set of the ALL Challenge dataset of ISBI 2019 (which is available here). Of those 1700 images, there were an equal number of images with healthy cells and images with ALL cells. 60% of those images were used to train the model, 20% of those images were used for the cross validation set, and 20% of those images were used for the test set. The model used in the study generally outperformed the VGG16, ResNet50, and the InceptionV3 models on the cross validation set, in which it achieved an accuracy of 92.35%, a sensitivity of 0.927, a specificity of 0.918, and an F1 score of 0.932. The goal of this study was to verify that the developed algorithm could be utilized by hospitals and doctors to better treat the thousands of people suffering with ALL across the world, many of whom are children.
mahima8178/Application_of_FFT_with_FIR_filter
This project will walk you through the importance of Fast Fourier Transform (FFT) which is one of the major computation techniques in the world of Digital Signal Processing (DSP). It also explains how 'Filter Design Toolbox' can be made use of in MATLAB to design desired filters on the go.
mahima8178/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
mahima8178/awesome
😎 Awesome lists about all kinds of interesting topics
mahima8178/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
mahima8178/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
mahima8178/deep-learning-time-series
List of papers, code and experiments using deep learning for time series forecasting
mahima8178/DeepLearning
A collection of research papers, datasets and software on Deep Learning
mahima8178/facenet-1
Face recognition using Tensorflow
mahima8178/Facial-Expression-Recognition-Classifier-Model
An Exciting Deep Learning based Flask web app that predicts the Facial Expressions of users and also does Graphical Visualization of the Expressions !
mahima8178/Goodreads_100k_books-Analysis-and-Recommendation
mahima8178/Google-Product-Reviews-Scrape-Analyse
mahima8178/labyrinth-algorithms
Explanation for various algorithms that are used for pathfinding.
mahima8178/mealpy
A collection of the state-of-the-art MEta-heuristics ALgorithms in PYthon (mealpy)
mahima8178/ML_tutorials
ML_tutorials
mahima8178/models
A collection of pre-trained, state-of-the-art models in the ONNX format
mahima8178/pandas_exercises
Practice your pandas skills!
mahima8178/Q-Learning-Maze-Treasure-HuntH
mahima8178/segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
mahima8178/stablediffusion-v2
High-Resolution Image Synthesis with Latent Diffusion Models
mahima8178/system-design-resources
These are the best resources for System Design on the Internet
mahima8178/t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
mahima8178/Text2Video-Zero
Text-to-Image Diffusion Models are Zero-Shot Video Generators
mahima8178/tobenamed
mahima8178/TransUNet
This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.