Deep Learning for Portfolio Optimization Zihao Zhang, Stefan Zohren, Stephen Roberts We adopt deep learning models to directly optimise the portfolio Sharpe ratio. So, … Learn. Our team Includes professors, PhD and MS students worldwide. Credits: Statista. This course covers several technique in a practical manner, the projects include but not limited to: (1) Train Deep Learning techniques to perform image classification tasks. The folio presents the collection of projects and allows review of individual projects. ⚡ Experience working on multiple cloud platforms. Deep Learning. Data Science & AI. Its goal is to facilitate research of networks that perform weight allocation in one forward pass. Research. Image regeneration for old damaged reel picture. In this post, you will discover how you can use small projects to demonstrate basic competence for using deep learning for predictive modeling. Through ProjectPro live classes, you will learn deep learning by implementing deep learning projects with TensorFlow using Python that you can showcase to the interviewers. Portfolio projects are one of the best ways to display your skills to a potential employer, especially to land your first entry level job in the field. I also Machine-Learning-Portfolio This is a repository of the projects I worked on or currently working on. Remember, it is important to showcase projects on your portfolio if you are a beginner in the field of data science and don’t have a degree or master’s in the subject. The framework we present circumvents the requirements for forecasting expected returns and allows us to directly optimise portfolio weights by updating model parameters. Instead of selecting individual assets, we trade Exchange-Traded Funds (ETFs) of market indices to form a portfolio. A machine learning portfolio is a collection of completed independent projects, each of which uses machine learning in some way. Deep Learning Projects This repository contains all Deep Learning Projects completed by me. Deep learning projects Credit card fraud detector This portfolio is a compilation of notebooks which I created for data analysis or for exploration of machine learning algorithms. Nutrition and Unsupervised Learning. Sudoku Solver in C++ with QT GUI. Projects - Kharpann. Portfolio of Machine Learning projects completed by me for academic, self-learning, and hobby purposes. Hyper customizable banking solutions with low code. A separate category is for separate projects. ⚡ Experience hosting and managing websites. It is a very frequent topic for movies, books, researchers, and all other media. Projects: Responsible for implementing dataset creation, transfer learning, training neural networks and device testing for tasks such as semantic/instance segmentation, object detection, and video segmentation using TensorFlow, Keras, MXNet and Caffe. Face Recognition. My complete implementation of assignments and projects in CS224n: Natural Language Processing with Deep Learning by Stanford (Winter, 2019). I know, how time- consuming and painful it is to … Neural Machine Translation: An NMT system which translates texts from Spanish to English using a Bidirectional LSTM encoder for the source sentence and a Unidirectional LSTM Decoder with multiplicative attention for the target sentence ( GitHub ). Multi-label Sound Event Retrieval. Cloud Infra-Architecture. Affective Movement Recognition and Generation. Flight Ticket Price Predictor using Python. In this series will cover some of the most interesting python projects that you can build today and add them to your portfolio. Visualizing Flags of the World. Facial Emotion Detection using Neural Networks. It is delivered in a unique 5-step learning process of LIVE online interactive sessions by IISc and TalentSprint faculty, capstone projects which start in the middle of the programme and continue till the end, mentorship, case studies, and campus visits to ensure fast-track learning. Bike Share Data and Machine Learning. All of these are relatively easy projects … Page template forked from evanca. Connect with recruiters You will build an online project portfolio, containing your deep learning project source code and video explaining your project. The second thing that you should understand is that there are jobs that have more generalist requirements like data analysis. Look here for a collection of my latests projects, exercises, articles, and more. Data Analytics. We’ll teach you the most in-demand ML models and algorithms you’ll need to know to succeed as an Machine Learning Engineer. Here are a few screenshots that I’ve captured from a few big (Facebook, Net… in the live video footage with around 93 percent accuracy. In this article many advanced AI algorithms for portfolio management and asset allocation are shown alongside their source code and evaluations on the datasets. Netflix Artwork Personalization Using AI (Advanced) Netflix is the dominant force in entertainment … Bitcoin is the very first decentralized digital … ⚡ Experience with 10+ Projects. In the literature, different DL models exist: Deep Multilayer Perceptron (DMLP), CNN, RNN, LSTM, Restricted Boltzmann Machines (RBMs), Deep Belief Networks (DBNs), and Autoencoders (AEs). deepdow (read as "wow") is a Python package connecting portfolio optimization and deep learning. About Interests: using machine learning for anything other than cats vs dogs Currently building ML projects for my portfolio and studying deep learning / reinforcement learning. It provides high-level abstraction for data modeling [21] . Music generation using deep learning. Movement Computing Affective Computing Deep Learning Dataset Experiments Machine Learning Projects Systems. 4th Vector Technologies portfolio of successful projects tackling many challenges, listed by inspection type, industry, and technology. Presented in the form iPython Notebooks. Machine Learning. Named Entity Recognition from Resumes. Designed a deep learning and computer vision-based surveillance system which can locate and make predictions about any violent weapon like Gun, Knife, Rifle, etc. Download it from the WaveMaker website now. Five properties of an effective machine learning portfolio include: Chess in Python with AI Opponent. Developing a portfolio of completed small projects allows you to demonstrate your ability to develop and deliver skillful models. Using a systematic five-step project template to execute projects and a nine-step template for presenting results allows you to both methodically complete projects and clearly communicate findings. By completing the AI program, you will be able to master essential DL theory, build hands-on projects, harness Deep Learning Reinforcement Learning Portfolio About Me Software Projects Parking sign detection and recognition Description: Parking signs in Australia are notoriously complicated. Music is an assortment of tones of various frequencies. For each model, you will learn how it works conceptually first, then the applied mathematics necessary to implement it, and finally learn to test and train them.