#100daysofml resultados da pesquisa
Day 41 of #100DaysOfML >>Kernel PCA today — where dimensionality reduction stops being linear and starts being clever. Took ordinary data: → Fired it through a feature map → Watched nonlinear structure snap into focus Crazy how swapping a kernel changes the entire geometry.
📅 Day 49 – Complete DS, ML, DL & NLP Bootcamp 🔹 Learned more about parallel programming in Python: • Used ProcessPoolExecutor for CPU-heavy work • Tried ThreadPoolExecutor for I/O tasks • Practiced with factorial calculations & a mini web-scraper #100DaysOfML #Python
Day 23 of my ML Journey 🚀 Focused on working and revising my previous ML topics & projects Currently continuing my work on: Fake News Prediction using Machine Learning with Python #100DaysOfML #MachineLearning #FakeNewsDetection
(Day 2/100) Learned about: 🔹 Challenges in ML 🔹 Applications of ML 🔹 ML Development Life Cycle 🔹 Jobs in the ML field (ignore my handwriting 😭) #100DaysOfML #MachineLearning #AI #DataScience #BuildInPublic #100DaysOfCode #AICommunity #LearningInPublic
Day 24 of #100DaysOfML Today, I continued building my CNN project focused on detecting diseases in apple plantations. Most of my time went into data preparation — cleaning, organizing, and setting up my dataset properly. #TensorFlow #CNN #AI #DataScience #LearningJourney
Day 22of my ML Journey 🚀 Started a new mini project: Fake News Prediction using Machine Learning with Python Working on data preprocessing & building models to classify news as real or fake #100DaysOfML #MachineLearning #FakeNewsDetection
Day 3 of my ML journey 🚀 I completed Week 3. So far I’ve learned: 📷 Problem With Overfitting 📷 Cost function with regularization 📷 Regularized Linear and Logistic Regression 📷 Andrew Ng and Fei-Fei Li discussion on Human Centered AI #MachineLearning #100DaysOfML #AI
📅 Day 48 – Complete DS, ML, DL & NLP Bootcamp 🔹 Learned: • Multithreading basics & practical usage • Multiprocessing for parallel tasks 🔹 Other: • Made a PPT & registered for coding competitions • Also did some college assignments #100DaysOfML #Python #Multithreading
📅 Day 51 – Complete DS, ML, DL & NLP Bootcamp 🔹 Started with Flask framework: • Understood WSGI (Web Server Gateway Interface) • Built a simple Flask app • Created routes like /home and /index 🕸️Also had some college assignment #100DaysOfML #Python #Flask #WebDevelopment
Back after a short break... Today I revised some of the basic Python Libraries, now diving into EDA yet again #100DaysOfML #DataScience #Python #MachineLearning #EDA #LearnInPublic #CodingJourney
mathematics and intuition involved in simple linear regression, whatever I understood. Ignore very bad handwriting, it's rough explanation. #100DaysOfML
Made my first ML model today 🎉(Day 4/100) Used dataset train my own ML model, used logistic regression for training. (ignore my handwriting 😭) #100DaysOfML #MachineLearning #AI #DataScience #BuildInPublic #100DaysOfCode #AICommunity #LearningInPublic
🛒 Day 56 – 100 Days of ML Built an E-commerce Product Recommendation System using CatBoost 💡 Learning from @geeksforgeeks Nation Skill-Up 👉Course: geeksforgeeks.org/batch/ds-16 #100DaysOfML #MachineLearning #CatBoost #RecommenderSystem #nationskillup #skillupwithgfg
Day 18 of my ML Journey 🚀 Completed my mini project: House Price Prediction using ML Applied regression models to predict housing prices based on different features Another step forward in practical ML learning! #100DaysOfML #MachineLearning #MiniProject
Day 51 of becoming an ML Beast 🦾 Wrapped up a simple ML project for practice Solved Leetcode problems Started learning Streamlit for ML deployment Also preparing for my Cyber Security exam #MachineLearning #LeetCode #100DaysOfML
✅ Just wrapped up Discretization in Machine Learning! Turned continuous features into meaningful bins 🧠📊 Great for tree models, better interpretability! Loving the power of feature engineering 🔥 #MachineLearning #DataScience #100DaysOfML (📸 attached: before & after magic!)
Day 1 of #100DaysOfML .. Finished: Introduction to Python (the last chapter) in #datacamp. Started: Intermediate Python.
I’m challenging myself to build discipline and complete #100DaysOfML ... on my way to becoming an ML Engineer! 🧪
Day 46 of #100DaysOfML - Learnt Outlier detection using Percentile and Winsorization Technique.
Day 45 of #100DaysOfML - Learnt Detection and removal of outliers using IQR proximity rule.
🚀 Day 63 – 100 Days of Machine Learning Journey Today, I explored Dimensionality Reduction 📘 Learn with @geeksforgeeks Nation SkillUp: 👉 Course: geeksforgeeks.org/batch/ds-16 #100DaysOfML #MachineLearning #PCA #LDA #DataScience #MLProjects #nationskillup #skillupwithgfg
Day 44 of #100DaysOfML - Learnt Outlier detection and removal using the Z-score method.
Day 43 of #100DaysOfML - Learnt basics about outliers. What are they.. etc. Most of the time went in clg work. Will do projects on weekends to practice.
🚀 Day 62 – 100 Days of Machine Learning Journey Today, I explored DBSCAN 📘 Learn with @geeksforgeeks Nation SkillUp: 👉 Course: geeksforgeeks.org/batch/ds-16 #100DaysOfML #MachineLearning #Clustering #UnsupervisedLearning #MLProjects #DataScience #nationskillup #skillupwithgfg
Day 42 of #100DaysOfML - Completed Iterative Imputation (MICE). The imputation part is finished.
👇🚀 Day 61 – 100 Days of Machine Learning Journey Today, I explored Hierarchical Clustering Learn with @geeksforgeeks Nation SkillUp: 👉 Course: geeksforgeeks.org/batch/ds-16 #100DaysOfML #MachineLearning #UnsupervisedLearning #MLProject #DataScience #nationskillup #skillupwithgfg
Re-ran a clean regression notebook for practice — ensuring proper scaling, evaluation (R², RMSE), and visualization. 📈 Great reminder that regression forms the foundation of predictive ML. #100DaysOfML #MachineLearning #Regression
Day 41 of #100DaysOfML - Learnt KNN imputer.. its quite interesting actually.
🚀 Day 60 – 100 Days of Machine Learning Today, I explored Advanced Clustering Algorithms like the Gaussian Mixture Model (GMM) 🎯 📘 Learn with @geeksforgeeks Nation SkillUp: 👉 Course: geeksforgeeks.org/batch/ds-16 #100DaysOfML #MachineLearning #nationskillup #skillupwithgfg
Day 56: Classification Recap 🤖 Wrapped up Classification! Covered: Logistic → KNN → Tree → Forest → Naive Bayes → SVM Explored tuning, evaluation & trade-offs between models. Next: Unsupervised Learning (Clustering) 🔍 #100DaysOfML #AI #MLJourney
Day 39 of #100DaysofML - Covered: Random Imputation, Missing Indicator, Automatic selection of parameters for imputation using GridSearchCV
🚀 Day 59 – 100 Days of Machine Learning Journey Today, I explored K-Means++, K-Mode, and Fuzzy Clustering 🤖 📘 Learn with @geeksforgeeks Nation SkillUp: 👉 Course: geeksforgeeks.org/batch/ds-16 #100DaysOfML #MachineLearning #MLProjects #DataScience #nationskillup #skillupwithgfg
Totally forgot to add — this one’s my Day 11 of #100DaysOfML 😅💻
Starting today, I'm learning Machine Learning/ Artificial intelligence in public. Goal: Build small analytical + ML projects and improve every week. If you're learning too, happy to connect. #100DaysOfML #DataScience #AI
Day 55: Model Comparison 📊 Compared all classifiers: Logistic | KNN | Decision Tree | Random Forest | Naive Bayes | SVM Metrics: Accuracy, F1-score, ROC-AUC 📊 Visualized results with a bar chart — SVM & Random Forest performed best! #100DaysOfML #DataScience
Day 15 of my ML Journey 🚀 Completed my mini project: Diabetes Prediction using Machine Learning with Python 🩺🤖 #100DaysOfML #MachineLearning #Python
Day 24 of #100DaysOfML Today, I continued building my CNN project focused on detecting diseases in apple plantations. Most of my time went into data preparation — cleaning, organizing, and setting up my dataset properly. #TensorFlow #CNN #AI #DataScience #LearningJourney
(Day 2/100) Learned about: 🔹 Challenges in ML 🔹 Applications of ML 🔹 ML Development Life Cycle 🔹 Jobs in the ML field (ignore my handwriting 😭) #100DaysOfML #MachineLearning #AI #DataScience #BuildInPublic #100DaysOfCode #AICommunity #LearningInPublic
📅 Day 49 – Complete DS, ML, DL & NLP Bootcamp 🔹 Learned more about parallel programming in Python: • Used ProcessPoolExecutor for CPU-heavy work • Tried ThreadPoolExecutor for I/O tasks • Practiced with factorial calculations & a mini web-scraper #100DaysOfML #Python
Day 18 of my ML Journey 🚀 Completed my mini project: House Price Prediction using ML Applied regression models to predict housing prices based on different features Another step forward in practical ML learning! #100DaysOfML #MachineLearning #MiniProject
Made my first ML model today 🎉(Day 4/100) Used dataset train my own ML model, used logistic regression for training. (ignore my handwriting 😭) #100DaysOfML #MachineLearning #AI #DataScience #BuildInPublic #100DaysOfCode #AICommunity #LearningInPublic
Day 10 of my ML Journey 🚀 1. Studied train_test_split method in detail 📊 2.Learned about Stemming in text preprocessing ✍️ Slowly connecting all the building blocks of ML! 🔥 #100DaysOfML #MachineLearning
🛒 Day 56 – 100 Days of ML Built an E-commerce Product Recommendation System using CatBoost 💡 Learning from @geeksforgeeks Nation Skill-Up 👉Course: geeksforgeeks.org/batch/ds-16 #100DaysOfML #MachineLearning #CatBoost #RecommenderSystem #nationskillup #skillupwithgfg
Day 3 of my ML journey 🚀 I completed Week 3. So far I’ve learned: 📷 Problem With Overfitting 📷 Cost function with regularization 📷 Regularized Linear and Logistic Regression 📷 Andrew Ng and Fei-Fei Li discussion on Human Centered AI #MachineLearning #100DaysOfML #AI
mathematics and intuition involved in simple linear regression, whatever I understood. Ignore very bad handwriting, it's rough explanation. #100DaysOfML
📅 Day 51 – Complete DS, ML, DL & NLP Bootcamp 🔹 Started with Flask framework: • Understood WSGI (Web Server Gateway Interface) • Built a simple Flask app • Created routes like /home and /index 🕸️Also had some college assignment #100DaysOfML #Python #Flask #WebDevelopment
Day 41 of #100DaysOfML >>Kernel PCA today — where dimensionality reduction stops being linear and starts being clever. Took ordinary data: → Fired it through a feature map → Watched nonlinear structure snap into focus Crazy how swapping a kernel changes the entire geometry.
📘 Day-(x+5) Today ML Progress ▫️ Learned Decision Tree Regression ▫️ CART minimizing MSE ▫️ Explored regularization & overfitting ▫️ Noted issues of axis sensitivity & variance Wrapped up with a few problem-solving tasks ✅ Next - RandomForest #AI #MachineLearning #100DaysOfML
Div, table, hover, text-shadow and box-shadow,. Learnt a new way to center a div using the width and margin property. #100daysofml #100DaysOfCode #consistency #day4
Day 5 of #100DaysOfML -done with Week 1! -currently working on hw problems. -this week's goal: Complete Chapter 3 of the handsonml book.
Day 44 of #100DaysOfCode 🚀 📖 Explored LLM models and their architectures. 📝 Solved a placement coding question: Valid Palindrome. 🤟✅ Completed my ML Project on Sign Language Detection — making AI more inclusive! #100DaysOfML #AI #DSA #LLM #MachineLearning
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