Faizy's repositories
09P_Detecting_COVID_19_with_Chest_X-Ray_using_PyTorch
Detecting COVID-19 with Chest X-Ray using PyTorch from COVID-19 Radiography Dataset on Kaggle
02P_Project_Image_Classification_with_CNNs_using_Keras
Training a CNN in Keras with a TensorFlow backend to solve Image Classification problems
Machine-Learning-Algorithms
This Repository consist of some popular Machine Learning Algorithms and their implementation of both theory and code in Jupyter Notebooks
04P-Classify-Radio-Signals-from-Outer-Space-using-Keras
The data we are going to use consists of 2D spectrograms of deep space radio signals collected by the Allen Telescope Array at the SETI Institute. We will treat the spectrograms as images to train an image classification model to classify the signals into one of four classes.
07P_Tumor-Diagnosis-Exploratory-Data-Analysis-on-Breast-Cancer-Wisconsin-DataSet
Tumor Diagnosis: Exploratory Data Analysis With Seaborn
ABigSurvey_NLP_ML
A collection of 300+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML)
M01_Mathematics_for-Machine_Learning_Linear_Algebra
Linear Algebra, Multivariate Calculus & PCA
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
tensorflow-3
TensorFlow Specialization 3 private repo, which will contains solution files.
the-incredible-pytorch
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
03P_Facial_Expression_Recoginition
Facial Expression Recognition with Keras!
05P_Understanding_Deepfakes_with_Keras_Using_DCGAN
Understanding Deepfakes with Keras
08P_COVID19_Data_Analysis_Using_Python
Data Analysis on COVID19 dataset, published by John Hopkins University
11P_Classification-with-Transfer-Learning-in-Keras
Classification with Transfer Learning in Keras
Blogging-Website-Using-Flask
This is the a Blogging Website created Using Flask
Deep-Learning
Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
machine_learning_examples
A collection of machine learning examples and tutorials.
Quantam-Machine-Learning
Quantum machine learning is an emerging interdisciplinary research area at the intersection of quantum physics and machine learning
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
TF01_Introduction-to-TensorFlow-for-AI-ML-and-DL
TensorFlow for building basic neural network for computer vision and use convolutions to improve your neural network.
TF02_Convolutional-Neural-Networks-in-TensorFlow
Tensorflow with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropouts
TF03_Natural-Language-Processing-in-TensorFlow
Solving Natural Language Processing problems with TensorFlow. Represent text through tokenization so that it’s recognizable by a neural network. Using RNNs, GRUs, and LSTMs, for NLP tasks and train them to understand the meaning of the text. Finally, we use Tensorflow to train LSTMs on existing text to create original poetry and more!
TF04_Sequences-Time-Series-and-Prediction
Using Tensorflow to solve time series and forecasting problems. Implement best practices to prepare data for time series learning & using RNNs and ConvNets for predictions. Finally, applying Tensorflow to build a sunspot prediction model using real-world data!
The-NLP-Pandect
A comprehensive reference for all topics related to Natural Language Processing
10P_Transfer-Learning-for-NLP-with-TensorFlow-Hub
we will use pre-trained NLP text embedding models from TensorFlow Hub, perform transfer learning to fine-tune models on real-world data, build and evaluate multiple models for text classification with TensorFlow, and visualize model performance metrics with Tensorboard.