Machine Learning Projects Blog

Machine Learning Projects Blog

Deep Learning Projects -See credential

  • Image-classifier from scratch that will identify different species of flowers

    Project image classifier from scratch that will identify 102 species of flowers build with Python, PyTorch, Numpy .

  • Predicting Bike-Sharing Patterns

    Learn neural network basics, and build your first network with PyTorch, NumPy, Pandas. Use the modern deep learning framework PyTorch to build multi-layer neural networks, and analyze real data. In this project, you’ll build and train your own Neural Network from scratch to predict the number of bikeshare users on a given day.

  • Dog Breed Classifier

    Learn how to build convolutional networks and use them to classify images (faces, melanomas, etc.) based on patterns and objects that appear in them. Use these networks to learn data compression and image denoising build with PyTorch , OpenCV, NumPy. We use OpenCV’s implementation of Haar feature-based cascade classifiers to detect human faces in images. In this project, you will learn how to build a pipeline to process real-world, user-supplied images. Given an image of a dog, your algorithm will identify an estimate of the canine’s breed.

  • Generate-TV-Scripts

    Build your own recurrent networks and long short-term memory networks with PyTorch, NumPy; perform sentiment analysis and use recurrent networks to generate new text from TV scripts.

  • Generate Faces

    Learn to understand and implement a Deep Convolutional GAN (generative adversarial network) to generate realistic images, with Ian Goodfellow, the inventor of GANs, and Jun-Yan Zhu, the creator of CycleGANs, buid with PyTorch, NumPy. Define two adversarial networks, a generator and discriminator, and train them until you can generate realistic faces

  • Deploying-a-Sentiment-Analysis-Model

    Train and deploy your own sentiment analysis model using Amazon’s SageMaker. Deployment gives you the ability to use a trained model to analyze new, user input. Build a model, deploy it, and create a gateway for accessing it from a website, buid with PyTorch, NumPy, Pandas, SageMaker.

  • Somalia UNHCR Patterns

    A neural network that predicts and compares the weekly Vegetation Health Index with the number of forced displacements of Somalia by using historical data as described here Build with PyTorch, NumPy, Pandas.

Computer Vision Projects-See credential

  • Facial expression recognition and Augmented Reality (AR)

    EmoAR is a mobile AR application (mobile device with ARCore support is required) that aims to recognize human facial expression in real time and to overlay virtual content according to the recognized facial expression , build with PyTorch, NumPy, herokuapp deploynement.

  • Facial Keypoint Detection

    Apply your knowledge of image processing and deep learning to create a CNN for facial keypoint (eyes,mouth, nose, etc.) detection, build with PyTorch, NumPy, OpenCV’s pre-trained Haar Cascade classifiers, Pandas.

  • Image Captioning

    Train a CNN-RNN model to predict captions for a given image. Your main task will be to implement an effective RNN decoder for a CNN encoder, build with PyTorch, NumPy, Microsoft Common Objects in Context (MS COCO) dataset.

  • Landmark Detection & Tracking (SLAM)

    Implement SLAM, a robust method for tracking an object over time and mapping out its surrounding environment, using elements of probability, motion models, and linear algebra, build with Python, NumPy,Pandas.

Deep Reinforcement Learning Projects -See credential