Fresh off the Databrick's #DataAI summit where our Data Science team presented some fascinating topics about simulating the SuperBowl and using rocket science in the betting world. 🚀 Excited to leverage machine learning and AI to drive value at DraftKings? We're always looking for talented data scientists ➡️ https://lnkd.in/ewyVvdVi
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🚀 Exciting News Alert! 🚀 I’m thrilled to share that my amazing team and I have hit a milestone in the world of machine learning! 🎉 We've just wrapped up a super cool project: a "Movie Recommendation System" 🎬🍿 Here's a sneak peek: 🔍 Data Preparation: We dove into the vast ocean of movie metadata from various sources on Kaggle, giving us a comprehensive database of movies up to 2020. After some serious scrubbing and cleaning, we were ready to roll! 🧼📊 🛠 Implementation: We went with a content-based approach for its simplicity and efficiency, leveraging cosine similarity to find out how movies relate to each other. Plus, this method helps us tackle the "cold start problem" due to a lack of user data. Who needs user data anyway? 😉✨ 💻 Interface: Using the Flask framework, we built a sleek interface with HTML and JavaScript to simulate a real website right on our local machine. Talk about bringing Hollywood to your home screen! 🌐🎥 Feel free to reach out if you want to chat about the project or just recommend your favorite movie! 📩🎬 Team Members 😎 Ahmed H.Almanfy Mohamed Momen Presentation Link : https://lnkd.in/dhMg3t8W #MachineLearning #AI #DataScience #MovieRecommendations #Flask #CosineSimilarity #TeamWork #Innovation
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Just dropped a blog post on the mythical creatures of the tech world: Full-Stack Data Scientists! 🦄 Ever wondered what they do? They're the Swiss Army knives in the data realm, juggling everything from data wrangling to model deployment. Check out my blog to unravel the mystery behind these versatile tech wizards. If you find it as enlightening as a data visualization chart, feel free to share! #datascience #ai #ds4tech https://lnkd.in/g4X4jth6
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Hey Data Scientists! Let's dive into some tech talk and settle the age-old debate: which data science library is your ultimate go-to? 📊 Whether you're Team Pandas, Tensorflow, or scikit-learn, it's time to share your secret sauce! So, what's your favourite? 📈 Vote and let's uncover the ultimate data scientist's toolkit together! 💼🔍 #DataScience #LibraryLove #TechDebate #libraries #ai #equinoxailab
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Check out this tutorial! Data Scientist Baraa Zaid outlines how to build a vector similarity-based video game recommender system using Milvus, FastAPI, and Docker, Inc. 🎮 https://bit.ly/495Pyyq #Milvus #DevCommunity #VectorDatabase
Building a Video Games Recommender System with Milvus, FastAPI, and Docker
blog.stackademic.com
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🚀 Today marks a significant milestone for me as I completed my inaugural machine learning project! 🤖📊 The task? Predicting California housing prices, a challenging yet rewarding endeavor. I delved deep into the world of data visualization, leveraging matplotlib and seaborn to gain insights and craft compelling visuals. The real thrill came during data preprocessing and feature engineering, where I fine-tuned the dataset to extract meaningful patterns. 🧐💡 Experimenting with different models was enlightening; starting with linear regression, which yielded a respectable 66% accuracy, and then implementing a random forest regressor, which significantly boosted performance to an impressive 82%! 🌟 This project has reinforced my passion for machine learning and data science. Excited for what's next on this journey! Check out the following link detailing this project: https://lnkd.in/dpHq9iAe #machinelearning #datascience #ai #ml #python #kaggle
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|| Data Science Enthusiast & Aspiring Machine Learning Engineer || Former Deputy Project Manager - Civil Engineer
Random Forest Classifier: Your Guide to Ensemble Power! An Attempt to capture the Robust randomness in a metaphor! - Data Bounty: The adventure begins with a treasure trove of data (squares) holding valuable information. - Diverse Rangers: Enter our team of colorful machines (decision trees/n_Estimators)! Each analyzes a single data point, using features as a map. - Exploration Depth: The green line represents how deep each ranger ventures (max_depth). Deeper dives (higher value) offer more details, but beware of getting lost! - Individual Calls: Based on their findings, each ranger "shouts out" a prediction (0 or 1). - Majority Wins: The rangers gather, with the most common prediction (1) becoming the final classification through voting. #DataScience #MachineLearning #RandomForestClassifier #DataAnalysis #DataMining #AI #ArtificialIntelligence #Python #DataAnalytics #BigData #PredictiveModeling #DataDriven #Statistics #DataScientists #ML #DeepLearning #Analytics #FeatureEngineering #DecisionTrees #EnsembleLearning #Classification #DataEngineering #DataVisualization #Algorithms #Tech
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I’m thrilled to share that I’ve completed the Data Science and Machine Learning: Making Data-Driven Decisions program at MiT Institute for Data, Systems and Society! Another deep dive into the data science world using python to navigate topics with hands-on projects on regression and prediction, deep learning, statistical analysis and recommendation systems. The program’s holistic approach has empowered me with an extensive knowledge base for making data-driven decisions, tackling complex challenges and driving impactful outcomes. Eagerly poised to apply this newfound, comprehensive understanding to real-world business scenarios! #ai #dataanytics #businessanalytics #pythonprogramming #datascience #recommendationsystem #hypothesistesting #deeplearning #continuouslearning
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STACK CHEATSHEET 🔥 A stack is an abstract data type that supports the operations push (insert a new element on the top of the stack) and pop (remove and return the most recently added element, the element at the top of the stack)👩💻 Stacks are an important way of supporting nested or recursive function calls and is used to implement depth-first search. Depth-first search can be implemented using recursion or a manual stack💻 ➡️ Check out here to know more 👇 ➡️ If you want to start your career into the field of data science, ML and AI visit here-- www.tutort.net #cheatsheets #stack #tutortacademy #command #codingpractices #codingchallenge
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🏠 Just launched an exciting machine learning project! 📊 Predicting Boston Housing Prices using ML and deployed it on Flask through Render. 📌 Key features: Explored diverse housing features like crime rates, accessibility to highways, and more. Implemented a regression model using Random Forest for accurate price predictions. Developed a user-friendly interface with Flask, making it accessible to anyone interested. 🔍 Insights and Impact: This project dug deep into the details of Boston's housing market. By looking closely at things like crime rates and accessibility to highways, the model not only achieved exceptional performance metrics, including a minimal Mean Squared Error (MSE), a near-perfect R-squared (R2), a low Mean Absolute Error (MAE), and a precise Root Mean Squared Error (RMSE), but also provided nuanced insights. 🚀 Check it out: [GitHub Link: https://lnkd.in/gC2T3TRX] 🙌 Acknowledgments: Grateful for the support and mentorship from Baishalini Sahu. Their guidance and insights played a crucial role in navigating the complexities of this project. Thankful for the collaboration and hard work of my teammates throughout this project. Their dedication and contributions were instrumental in achieving our goals 💡 Next Steps: Eager to continue exploring the vast possibilities in the field of machine learning and data science. Open for discussions on this project or similar ventures. Let's connect and stay curious together! #MachineLearning #DataScience #FlaskApp #BostonHousing #AI #ProjectShowcase #ITT
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