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