Machine learning portfolio github example. md at Add this topic to your repo.

Once you've done this, git is setup and configured. Project 1: Data cleaning. Jan 13, 2020 · My GitHub Page. Consultantcy project for 4theplayer. Reload to refresh your session. This repository showcases a collection of machine learning projects in various domains, demonstrating my skills and expertise as a data scientist and machine learning engineer. FinRL has three layers: market environments, agents, and applications. ML theory analysis: linear regression. For practical application see the repository: Machine-Learning-for-Asset-Managers-Oslo-Bors. The hope is that this paper will organically Repository for my machine learning projects. This repository is our attempt at utilising machine learning methods to create a sparsified and optimized portfolio that will perform well into the future. e two digit) then it will classify as yes. pdf/sample_presentation. The notebooks to this paper are Python based. Effect of Game Theoretical Margin on Game Success. Each project provides step-by-step instructions, code, and visualizations to showcase the data analysis and modeling techniques employed. main May 12, 2021 · Step 3 — Hosting on Github. You signed out in another tab or window. By the end of this specialization, you will have acquired the tools required for making Jan 2, 2024 · When your site is built, Jekyll will use the URL you specified, rather than the default one provided by GitHub. Pyfolio facilitates the analysis of portfolio performance and risk in-sample and out-of-sample using many standard metrics. The pieces of my Machine Learning experiences are already quite scattered, so here is a place that brings them all together in one place. Different methods can be applied with each has its own trade-offs. Student, Software Engineer, and AI/ML Researcher. 0001. A great machine learning portfolio is a collection of industry-standard machine learning projects that can prove that a candidate has all the required machine learning skills. 91) and that smaller particles are better estimated than larger ones. Machine Learning Portfolio. Data processing including nesting/unnesting, statistical analysis, linear regression, seaborn. " GitHub is where people build software. pdf; You can also visit the original tutorial with more Contribute to jwsoh07/machine-learning-portfolio development by creating an account on GitHub. Jul 5, 2016 · This project on Github. Python机器学习项目实战. Portfolio of machine learning projects completed for academic & self-learning purposes. Roadmap Portfolio in this repo is presented in the form of . name YOUR_NAME. The Machine Learning basics program is designed to offer a solid foundation & work-ready skills for machine learning engineers, data scientists, and artificial intelligence professionals. ) should be indent with two space below github:. I am grateful of the 30-day free trials and discounts given by Udacity during the difficult times of #COVID19, encouraging programming enthusiasts like myself to enjoy the time of #STAYHOME. Small projects constrained in effort and resources can keep velocity high. This will become the content of your Portfolio of projects completed by me for academic, self learning and hobby purposes. Once that’s done, commit the changes. If you run the logistic_regression. To associate your repository with the python-machine-learning topic, visit your repo's landing page and select "manage topics. As discussed in the training video, the standard train-test procedures for machine learning are not well suited for portfolio optimization. 0%. Step 3) Fill out README. Each folder represents the fields of application (i. The third step is to fill out your README. Videos FinRL at AI4Finance Youtube Channel. Machine Learning Skills learned Jan 8, 2024 · Maggie has created an excellent example of a clear, attractive, accessible GitHub portfolio site. machine-learning-algorithms. ipynb. Tools. Publication. The final step is to create a new repository on Github. NET framework in the Machine Learning My skills include data analysis, visualization, and machine learning. Creating a website or app that someone can interact with. Oliver's machine learning portfolio is compromised of three programs (Grade Predictor, K-NN Diabeties Predictor, and KMeans) that dive deep into supervised and unsupervised learning concepts through the algorithms of linear regression, clustering, and k-nearest neighbor in each respective program. Used Matlab to train over 100 machine learning models which estimated particulate matter concentrations based on a suite of over 300 biometric variables. Contribute to Lala2398/Machine-Learning-Portfolio development by creating an account on GitHub. This is a repository of select machine learning and data analysis projects completed for academic purposes, as examples of my data science work. NET apps. You switched accounts on another tab or window. The first group of data I trained on, for 2000 iterations and a learning rate of 0. Building a dashboard around a specific dataset or topic. A newbie who wants to learn machine learning algorithm with Python. You signed in with another tab or window. Sep 27, 2016 · Benefits for You. - chribsen/simple-machine-learning-examples Identification of trends in the stock prices of a company by performing fundamental analysis of the company. The fundamental issue is the rules of the game keep evolving for portfolio optimization. To associate your repository with the machine-learning-projects topic, visit your repo's landing page and select "manage topics. I'm a graduate of MIT's Class of 2018 and my passion is Computer Science. About. This platform has many courses in many fields such as Data Science, Machine Learning, Deep Learning, Artificial Intelligence, etc. Contribute to Abhishek3794/portfolio development by creating an account on GitHub. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Be the first to add your personal Used ** Matlab ** to train over 100 machine learning models which estimated particulate matter concentrations based on a suite of over 300 biometric variables. Welcome to my data analytics / science portfolio. It offers a unified interface and tools compatible with scikit-learn to build, fine-tune, and cross-validate portfolio models. Our aim is to provide an inference platform Data Science and Machine Learning Portfolio. Note: You must remove the site. The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions. Next, we need to create an account on GitHub, then configure git to work with GitHub: Create a GitHub account. Else it will classify as no. Contribute to cumse/Machine-Learning-Portfolio development by creating an account on GitHub. Udacity has many nanodegrees which are a series of courses in a specific field. Python Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). md: you can modify it to the description of your page. I often work on end-to-end data science projects that usually begin from collecting data from third party sources and end with delivering business insight in the form of customer segments. I covered everything you need, to build regression system and a lot of tools & techniques, that are common in the machine learning landscape. MIT '18, M. com. System simply classifies the data with it's sum, If the sum of integers given as data is greater than 10 (i. Oliver's ML Portfolio. This python module provides code for training popular clustering models on large datasets. Note: Data used in the projects is for learning and demo purposes only. Finding Good Data Sets. I generated some random normal data and used scikit's test/train split tool to separate my data into two groups. R and . Essentially, it adds a penalty (parameterised by gamma) on small weights, with a term that looks just like L2 regularisation in machine learning. Udacity is a for-profit educational organization which offering massive open online courses (MOOCs). ML. In this project I attempt to clean a database then use machine learning to predict the prices of the To associate your repository with the developer-portfolio topic, visit your repo's landing page and select "manage topics. Python. Add this topic to your repo. For the test portfolio of 20 securities, gamma ~ 1 is sufficient Machine-Learning-Portfolio This repository displays the current projects that I have worked on related to Data Science, Machine Learning, and AI. We'll make extensive use of Pandas DataFrames, which make it easy to read in and work with tabular data in Python. Focus: Each project has a well-defined purpose and end point. This repository is updated regularly with new projects and coursework. In this GitHub repo, we provide samples which will help you get started with ML. A project with 📜 means I had some external help (project as part of a course or help from a teacher). 1. io. Academics. Don’t confuse the simplicity for the work of a rookie—this is a thoughtful site, showing a bit about her, her CV/resume, portfolio projects, and her related passions of the talks she gives as well as some blog articles exploring her journey Add this topic to your repo. Gain hands-on experience in data preprocessing, time series, text mining, and supervised and unsupervised learning. To evaluate and compare different strategies or to improve an existing strategy, we need metrics that reflect their performance with respect to our objectives. By last count there are about 15 distinct trading varieties and around 100 trading strategies. This example defines a function 'preprocess()' which will perform sentence and word tokenization, part of speech tagging, and named entity chunking on input text. sql. To associate your repository with the financial-machine-learning topic, visit your repo's landing page and select "manage topics. md file. Dive in to uncover insights and explore techniques in data science. Applied unsupervised deep learning approaches to longitudinal ICU data So instead of letting your neural network learn an arbitrary function, you are learning the parameters of a probability distribution function modeling your data. We'll use our editing tools along with libraries like Pandas and scikit-learn in this post. It covers a broad range of ML techniques from linear regression to deep reinforcement learning and demonstrates how to build, backtest, and evaluate a trading strategy driven by model predictions. Anyone wishes to move beyond the basics and develop an understanding of the whole range of machine learning algorithms. Other 0. I am a passionate Machine Learning Engineer with a strong foundation in data science and artificial intelligence. This Repository contains portfolio of Machine Learning projects for academic, self learning and work purposes, presented in the form of iPython Notebooks. This repo contains simple machine learning examples using scikit-learn and Python. Having completed your minimalism portfolio, you now can remove or modify these files in your repository: LICENSE; README. Repository containing portfolio of data science projects completed for academic, self learning, and professional purposes. Contribute to atabti/Machine-Learning-Portfolio development by creating an account on GitHub. github. Note: Please open issues related to ML. To load the Machine Learning example data, run the following command in 'data' directory of the cloned repository: $ vsql -f load_ml_data. skfolio is a Python library for portfolio optimization built on top of scikit-learn. A Simple NLP Preprocessing Pipeline: An example showing how a function can be used to create a preprocessing pipeline for common natural language processing tasks. Exemplifies. python data-science machine-learning youtube statistics deep-neural-networks computer-vision deep-learning neural-network math tensorflow machine-learning-algorithms pytorch datascience tensorflow-tutorials data-science-portfolio tensorflow-examples pytorch-tutorial pytorch-implementation tensorflow2 Overview. NET and how to infuse ML into existing and new . Contribute to kevintoner/machineLearningPortfolio development by creating an account on GitHub. Apr 29, 2023 · Example config. If you sample points from this distribution, you can generate new input data samples hence why a VAE is considered as a "generative model". Jupyter Notebook 99. Source files for these (and the entire demo site) can be found in /docs. This is a repository consisting of projects for the Udacity Machine Learning Engineer Nanodegree Program. There is also a customized version of Zipline that makes it easy to include machine learning model predictions when designing a trading strategy. A quick start: Stock_NeurIPS2018. A good data set for an end to end machine learning project can be hard to find. Portfolio for machine learning sample projects . io ”. The dataset consists of approximately 24 million records in CSV format. To associate your repository with the machine-learning-regression topic, visit your repo's landing page and select "manage topics. For example, a GAN trained in a dataset of breast cancer images learns how to generate new images similar to those seen in the dataset. machine-learning-models. Eng. 2. There are three ways to install: as a gem-based theme, as a remote theme (GitHub Pages compatible), or forking/directly copying all of the theme files into your project. XGBoost classification and machine learning insights (Permutation Importance, Partial Dependence Plots, SHAP Values) [didactic code]. This paper investigates various machine learning trading and portfolio optimisation models and techniques. Overall, incorrect data is either removed, corrected, or imputed. 9%. skfolio. sample_page. Whether your interest lies in database management, data analysis, or the fusion of SQL with machine learning techniques, this repository serves as a curated collection that encapsulates my skill set Add this topic to your repo. In investment and trading, the most common objectives are the return and the risk of the investment portfolio. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. NET is a cross-platform open-source machine learning framework that makes machine learning accessible to . For me, that would be “ kurtispykes. It produces tear sheets covering the analysis of returns, positions, and transactions, as well as event risk during periods of market stress using several built-in scenarios, and also includes Bayesian out-of-sample Add this topic to your repo. Be the first to add your personal experience. md at Add this topic to your repo. My interests include software design and development, artificial intelligence, machine learning, computer vision, and natural language processing. Alternatively, you can run the indiviudal commands in the SQL file to load a particular data set. Last Words. finance data-science machine-learning time-series trading data-visualization cryptocurrency portfolio-optimization trading-strategies quantitative-finance algorithmic-trading backtesting quantitative-analysis algorithmic-traiding Housing Prices with California Housing Dataset: In this notebook I explained how to tackle a machine learning from the beginning to the end, at the example of predicting housing prices. More projects are in progress and will be added here when complete. . readme file presented below. Jupyter Notebook 100. This field is closely related to artificial intelligence and computational statistics. December 4, 2020. Follow GitHub links for code and documentation. Note that although these notebooks focus on a specific framework, the same approach works with all the frameworks that Amazon SageMaker Debugger supports. Knowledge Base: The corpus of completed projects provide a My portfolio features the following projects: Text reading complexity prediction with transformers ; 溺 Image-to-text translation of chemical structures with deep learning Fair machine learning in credit scoring applications ; Click "read more" to see project summaries. To leverage Github Pages hosting services, the repository name should be formatted as follows your_username. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. Analyzing data on a trending topic such as a popular tv show or news story. We focus on Bayesian nonparametric models based on the Dirichlet process, but also provide parametric counterparts. How to measure portfolio performance. For a trading task (on the top), an agent (in the middle) interacts with a market environment (at the bottom), making sequential decisions. Machine Learning. Image by author. main Languages. NET developers. Choose your projects wisely. An interesting analogy is a game playing DRL model. In this article, I will introduce you to 20 machine learning projects for portfolio solved and explained with Python. For more information, see the Jekyll variables documentation. My Introduction. Machine learning is the practice of teaching a computer to learn. In this project I predict English and Welsh house prices in 2015 from historical data (1995-2014) using only the length of the lease, type of property (flat, terrace etc) and if the house is in London. prefix, and each variable name (after the github. Host and manage packages Security Dominant machine learning type: Training data: 1: Which projects will succeed ? Classification: Supervised learning: Project lists, identifying which have succeeded, with additional columns of features that may be relevant: 2: Which engagements will succeed ? Classification: Supervised learning: Engagement lists, as above: 3: Which prospects This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. md: you can remove or change it to a blog post. For instance when a DRL is trained for chess, the rules never change. It is distributed under the open source 3-Clause BSD license. To associate your repository with the portfolio-management topic, visit your repo's landing page and select "manage topics. I'm currently a graduate student working Machine Learning Portfolio. Presented in the form of Jupyter Notebooks. Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning - mgroncki/IPythonScripts Languages. Installation, data sources and bug reports The code examples rely on a wide range of Python libraries from the data science and finance domains. Each of the below projects are presented in the form of Jupyter Notebooks. . 1%. bnpy supports the latest online learning algorithms as well as standard offline methods. yml file. e. I have developed a strong acumen for problem solving, and I enjoy an occasional challenge. Topics python finance machine-learning research trading investing portfolio-optimization quantitative-finance algorithmic-trading portfolio-management financial-machine-learning Dec 4, 2020 · Aman Kharwal. We found biometric variables can be used to accurately estimate particulate matter concentrations at ultra-fine spatial scales with high fidelity (r2 = 0. Additional sample posts are available under posts archive on the demo site. - tushar2704/ML-Portfolio I am an experienced "traditional" software engineer switching to a career as a Machine Learning Engineer. Building up a collection of completed machine learning projects can keep you focused, motivated and be leveraged on future projects. These examples provide and introduction to SageMaker Debugger which allows debugging and monitoring capabilities for training of machine learning and deep learning algorithms. MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools. Tools used: Sanketp1997 / Simple-Machine-Learning-Implementation-Using-Keras. Contribute to YeJiu97/machine-learning-bookcamp-build-a-portfolio-of-real-life-projects development by creating an account on GitHub. It may be necessary to try several gamma values to achieve the desired number of non-negligible weights. Powered by AI and the LinkedIn community. Installation. Table of contents. Delve into a diverse collection of projects showcasing machine learning and data analysis. Original Projects; My External Links; Posts; Courses and Certifications Examples of code-based projects include: Scraping a dataset and performing some analysis or training a model. To associate your repository with the data-science-portfolio topic, visit your repo's landing page and select "manage topics. - Machine-Learning-Portfolio/README. To associate your repository with the stock-price-prediction topic, visit your repo's landing page and select "manage topics. Timeseries, Deeplearning, MachineLearning, etc) For a detailed code example and images, please refer to . Armed with a Master's degree in Machine Learning from DCS (Rolwala), I thrive on solving complex problems using cutting-edge technologies. Replace YOUR_NAME with your full name, like John Smith . Follow the machine learning workflow. Analysis of online slot games. Sentiment score was computed by calculating the difference between positive and negative words present in the news Welcome to my data analytics / science portfolio. With six new chapters, on topics including movie recommendation engine development with Naive Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Data cleaning involve different techniques based on the problem and the data type. To associate your repository with the data-analysis-project topic, visit your repo's landing page and select "manage topics. Python: NumPy, Pandas, Seaborn, Matplotlib; Machine Learning: scikit-learn, TensorFlow, keras Eric Wadkins. This book aims to show how ML can add value to algorithmic trading strategies in a practical yet comprehensive way. Portfolio optimization is a process of allocating funds into financial assets with the goal of maximizing returns over risk. Note: In chapter 4 - there is a bug in the implementation of "Optimal Number of Clusters" algorithm (ONC) in the book (the code from the paper - DETECTION OF FALSE INVESTMENT STRATEGIES USING UNSUPERVISED LEARNING METHODS, de Prado and Lewis (2018) - ML Portfolio. Rmd (R-markdown) files. My journey has been marked by hands-on experience in projects ranging GAN is a machine learning model that can learn how to replicate the properties of a dataset. py file, the following example will use this data. Organized by project, each directory offers comprehensive access to code, datasets, detailed documentation, and resources. Data Science Consultant @ Shawhin Talebi Ventures LLC (December 2020 - Present) Conducted data collection, processing, and analysis for novel study evaluating the impact of over 300 biometrics variables on human performance in hyper-realistic, live-fire training scenarios. Code and data are made available where appropriate. We fit a least squares regression (with elastic net regularisation). Machine Learning Projects. [link] Keywords (Tensorflow, Sklearn, Deep learning, MLP, Naive Bayes, XGBoost , ML insights, Classification) Furthermore, I've woven in insights from diverse data analytics courses, illustrating the symbiotic relationship between SQL and machine learning. It’s better to look at it on this link instead of on github. Anyone who has a deep interest in the practical application of machine learning to real world problems. - memr5/Machine-Learning-Portfolio Jan 14, 2017 · Set up your git name by typing git config --global user. This is a very Simple Machine Learning Example Implemented with Keras model. gi ea ej xn vy oh pz uy xm mj