{"id":893,"date":"2023-04-20T10:42:18","date_gmt":"2023-04-20T10:42:18","guid":{"rendered":"https:\/\/www.analyticsvidhya.com\/datahack-summit-2023\/?page_id=893"},"modified":"2023-08-11T18:31:05","modified_gmt":"2023-08-11T13:01:05","slug":"applied-machine-learning","status":"publish","type":"page","link":"https:\/\/www.analyticsvidhya.com\/dhs-2023\/workshop\/applied-machine-learning\/","title":{"rendered":"Applied Machine Learning with Generative AI"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Unlock the power of machine learning with Generative AI and discover how it can revolutionize your approach to solving business problems. Join us for this immersive workshop, meticulously crafted to equip you with the knowledge, tools, and techniques necessary to excel in machine learning with Generative AI. Through engaging real-life case studies, you will witness how industry experts leverage machine learning to drive success and also understand how to make use of Generative AI tools as a part of the data science journey.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Throughout this 8-hour workshop, we will guide you through the essential modules that make up the machine learning pipeline. From data cleaning to feature engineering, model building, and evaluation, you will gain a comprehensive understanding of each stage. Additionally, we will teach you how to effectively frame a business problem as a machine learning challenge and guide you through the process of building, selecting, and evaluating models. Apart from this, you will master prompt engineering and learn the best practices to write effective prompts for data science tasks.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Workshop Highlights:<\/span><\/p>\n<h4><span style=\"font-weight: 400;\">Module 0: Introduction<\/span><\/h4>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Unveiling the essence of Machine Learning<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Exploring types of ML: Supervised, Unsupervised, Reinforcement<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Understanding ML problem types: Regression, Classification<\/span><\/li>\n<\/ul>\n<h4><span style=\"font-weight: 400;\">Module 1: EDA and Linear Models<\/span><\/h4>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Generating insights using EDA and Statistics<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Mastering Linear Regression<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Unleashing the potential of Logistic Regression<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Harnessing the power of Regularization (L1\/L2)<\/span><\/li>\n<\/ul>\n<h4><span style=\"font-weight: 400;\">Module 2: Prompt Engineering<\/span><\/h4>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">What is prompt engineering?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Understanding basic elements of prompts<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Different prompt engineering techniques<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tips and best practices to write effective prompts<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Learn best prompts for linear models<\/span><\/li>\n<\/ul>\n<h4><span style=\"font-weight: 400;\">Module 3: Model Evaluation<\/span><\/h4>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Navigating Training and Validation Models<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Exploring Evaluation Metrics: Accuracy, RMSE, ROC, AUC, Confusion Matrix, Precision, Recall, F1 Score<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Overcoming Overfitting and Bias-Variance trade-off<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Embracing K-fold Cross Validation<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Write effective prompts for model evaluation<\/span><\/li>\n<\/ul>\n<h4><span style=\"font-weight: 400;\">Module 4: Tree-based Models<\/span><\/h4>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Unraveling the intricacies of Decision Trees<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Harnessing the power of Bagging and Boosting<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Unleashing the potential of Random Forest<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Mastering Gradient Boosting Machines<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Discovering Feature Importance techniques<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Build effective prompts for tree based models<\/span><\/li>\n<\/ul>\n<h4><span style=\"font-weight: 400;\">Module 5: Model Selection<\/span><\/h4>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Streamlining Model Pipelines<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Unveiling the art of Feature Engineering<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Craft best prompts for feature engineering<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Don&#8217;t miss this opportunity to gain a competitive edge in the world of machine learning and transform your business strategies. Join us and embark on an enlightening journey towards data-driven success!<\/span><\/p>\n<p><strong>Pre-requisites: <\/strong><\/p>\n<ul>\n<li>System Requirement and Setup\n<ul>\n<li>Laptop with at least 4-8 GB of RAM<\/li>\n<li>We will be using Google Colab for the workshop, hence make sure you have a google login and space on your google drive<\/li>\n<\/ul>\n<\/li>\n<li>Offline Setup [Optional]\n<ul>\n<li>Install Anaconda (<a href=\"https:\/\/docs.anaconda.com\/anaconda\/install\/\" target=\"_blank\" rel=\"noopener\">Resource<\/a>)<\/li>\n<li>Install Python3.6 or above on Anaconda (<a href=\"https:\/\/docs.anaconda.com\/anaconda\/user-guide\/faq\/#anaconda-faq-35\" target=\"_blank\" rel=\"noopener\">Resource<\/a>)<\/li>\n<\/ul>\n<\/li>\n<li>Pre-reads\n<ul>\n<li>Programming knowledge in Python (Python: <a href=\"https:\/\/www.analyticsvidhya.com\/blog\/2016\/01\/complete-tutorial-learn-data-science-python-scratch-2\/\" target=\"_blank\" rel=\"noopener\">Resource<\/a>)<\/li>\n<li>Jupyter Notebook Environment familiarity (<a href=\"https:\/\/www.analyticsvidhya.com\/blog\/2018\/05\/starters-guide-jupyter-notebook\/\" target=\"_blank\" rel=\"noopener\">Resource1<\/a>, <a href=\"https:\/\/github.com\/amitkaps\/art-data-science\" target=\"_blank\" rel=\"noopener\">Resource2<\/a>)<\/li>\n<li>Basics of Machine learning (<a href=\"https:\/\/www.analyticsvidhya.com\/blog\/2017\/09\/common-machine-learning-algorithms\/\" target=\"_blank\" rel=\"noopener\">Resource<\/a>)<\/li>\n<li>Google Colab Intro (<a href=\"https:\/\/colab.research.google.com\/notebooks\/basic_features_overview.ipynb\" target=\"_blank\" rel=\"noopener\">Resource<\/a>)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>Note: These are tentative details and are subject to change.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Unlock the power of machine learning with Generative AI and discover how it can revolutionize your approach to solving business problems. Join us for this immersive workshop, meticulously crafted to equip you with the knowledge, tools, and techniques necessary to excel in machine learning with Generative AI. Through engaging real-life case studies, you will witness [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":1616,"parent":890,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"workshop-detail.php","meta":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Applied Machine Learning with Generative AI - DataHack Summit 2023<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.analyticsvidhya.com\/dhs-2023\/workshop\/applied-machine-learning\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Applied Machine Learning with Generative AI - DataHack Summit 2023\" \/>\n<meta property=\"og:description\" content=\"Unlock the power of machine learning with Generative AI and discover how it can revolutionize your approach to solving business problems. 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