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Coding, ML, GenAI, Qunat Engg!

145 following28 followers

The Achiever

Musa Qureshi is a dedicated coder and machine learning enthusiast on a relentless quest to master GenAI technology. Through persistent experimentation and continuous learning, Musa shares valuable insights and resources with a growing community. His journey embodies the spirit of perseverance and quality over speed in skill-building.

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658-248
$0.12
Likes
5-4
45%
Retweets
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Replies
6-3
55%
Bookmarks
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Top users who interacted with Musa Qureshi over the last 14 days

@aditiloves29

collabsclub.com - Collab with brands Next cooking - devsearch.tech Buy me a coffee - buymeacoffee.com/aditiloves29

2 interactions
@bhoomi404

Figuring out design, code, life, and what to tweet next ✨

1 interactions
@askshashanka

Indie Builder who saves MVPs from death by diagnosis and iteration | MVP Rescue Engineer

1 interactions
@OjasSharma276

21, Always Building and Learning

1 interactions

Musa’s dedication to learning is inspiring, but at this rate, his GenAI projects might reach production faster than his tweet likes—good thing machines don’t need social validation!

Successfully completed and extended a #100DaysOfML challenge, mastering advanced machine learning techniques and turning a public learning effort into a practical project repository.

To become a proficient leader in GenAI and Quantitative Engineering by learning publicly, contributing practical projects, and inspiring others through his educational journey.

Musa believes that mastery is achieved through consistent effort, hands-on practice, and sharing knowledge openly to uplift the learning community. He values quality learning experiences and believes that struggle is an essential part of growth.

Musa’s greatest strength lies in his disciplined, methodical approach to learning and his ability to document and share that journey, making complex topics accessible to others.

Despite producing valuable content, Musa’s low tweet engagement and follower count indicate a challenge in connecting with and expanding his audience on X.

To grow his audience on X, Musa should boost interaction by engaging actively with the ML and GenAI community through replies, collaborations, and regular Q&A sessions. Adding a personal touch or storytelling to his technical posts could also increase relatability and follower engagement.

Fun fact: Musa stretched his #100DaysOfML challenge to 134 days to deepen his understanding of complex ML models like XGBoost and ensemble methods, showing his commitment to quality over speed!

Top tweets of Musa Qureshi

Days 127-134: XGBoost & Advanced ML - Complete! 🎉 Completed videos 127-134 from @CampusX_official XGBoost algorithms DBSCAN Clustering Imbalanced Data Hyperparameter Tuning ROC-AUC Curves 100+ Days Complete! 💯 #100DaysOfML #MachineLearning #DataScience #GSoC2026

23

Days 116-123: SVM & Naive Bayes Completed videos 116-123 from @CampusX_official Kernel Trick in SVM Conditional Probability Independent Events Mutually Exclusive Events Bayes Theorem Problem solving #100DaysOfML #MachineLearning #DataScience #GSoC2026

16

🎯 Days 108–115: Advanced ML Algorithms Completed videos 108–115 from @CampusX_official Gradient Boosting Stacking & Blending Ensembles Agglomerative Hierarchical Clustering K-Nearest Neighbors Assumptions of LR #100DaysOfML #MachineLearning #DataScience #CampusX #AI #GSoC2026

14

Days 100-107: Boosting & Clustering Completed videos 100-107 from @CampusX_official Adaboost from scratch Hyperparam tuning Bagging vs Boosting K-Means Clustering Python implementatn Gradient Boosting Boosting mathematics #100DaysOfML #MachineLearning #DataScience #GSoC2026

15

Days 91-98: Random Forest & Boosting Completed videos 91-98 from @CampusX_official Random Forest algorithm Bias-Variance Trade-off Hyperparameter tuning GridSearchCV OOB Score Feature Importance Adaboost Classifier #100DaysOfML #MachineLearning #DataScience #GSoC2026

14

Days 83-90: Ensemble Learning Techniques Completed videos 83-90 from @CampusX_official Decision Tree visualization Ensemble Learning Voting methods Hard & Soft Voting Bagging techniques Bagging Classifiers & Regressors #100DaysOfML #MachineLearning #DataScience #GSoC2026

18

Days 74-80: Classification & Decision Trees Completed videos 74-80 from @CampusX_official Gradient Descent Confusion Matrix Precision, Recall, F1 Softmax Regression Polynomial features Hyperparameters Decision Trees #100DaysOfML #MachineLearning #DataScience #GSoC2026

17

Days 70-80: Regularization & Logistic Regression Completed videos 66-72 from @CampusX_official Lasso & ElasticNet Regression Logistic Regression basics Perceptron Trick Sigmoid Function Loss functions #100DaysOfML #MachineLearning #DataScience #GSoC2026

17

Days 60-70: Gradient Descent & Advanced Regression Completed videos 56-62 from @CampusX_official Gradient Descent variants Batch & Stochastic methods Polynomial Regression Bias-Variance Trade-off Ridge Regression #100DaysOfML #MachineLearning #DataScience #GSoC2026

16

Days 50-60: PCA & Linear Regression Completed videos 49-55 from @CampusX_official PCA visualization Simple Linear Regression Mathematical formulation Regression metrics (MSE, MAE, R2) Multiple Linear Regression #100DaysOfML #MachineLearning #DataScience #GSoC2026

13

Days 40-50: Outlier Detection & Feature Engineering Completed videos 40-46 from @CampusX_official MICE Algorithm Outlier detection methods Z-score & IQR Winsorization Feature Construction Curse of Dimensionality #100DaysOfML #MachineLearning #DataScience #GSoC2026

14

Days 30-40: Advanced Feature Engineering & Data Handling Completed videos 31-40 from @CampusX_official Power Transformations Binning & Binarization Mixed Variables DateTime features Missing Data Imputation #100DaysOfML #MachineLearning #DataScience #GSoC2026

16

Most engaged tweets of Musa Qureshi

Days 127-134: XGBoost & Advanced ML - Complete! 🎉 Completed videos 127-134 from @CampusX_official XGBoost algorithms DBSCAN Clustering Imbalanced Data Hyperparameter Tuning ROC-AUC Curves 100+ Days Complete! 💯 #100DaysOfML #MachineLearning #DataScience #GSoC2026

23

Days 116-123: SVM & Naive Bayes Completed videos 116-123 from @CampusX_official Kernel Trick in SVM Conditional Probability Independent Events Mutually Exclusive Events Bayes Theorem Problem solving #100DaysOfML #MachineLearning #DataScience #GSoC2026

16

🎯 Days 108–115: Advanced ML Algorithms Completed videos 108–115 from @CampusX_official Gradient Boosting Stacking & Blending Ensembles Agglomerative Hierarchical Clustering K-Nearest Neighbors Assumptions of LR #100DaysOfML #MachineLearning #DataScience #CampusX #AI #GSoC2026

14

Days 100-107: Boosting & Clustering Completed videos 100-107 from @CampusX_official Adaboost from scratch Hyperparam tuning Bagging vs Boosting K-Means Clustering Python implementatn Gradient Boosting Boosting mathematics #100DaysOfML #MachineLearning #DataScience #GSoC2026

15

Days 91-98: Random Forest & Boosting Completed videos 91-98 from @CampusX_official Random Forest algorithm Bias-Variance Trade-off Hyperparameter tuning GridSearchCV OOB Score Feature Importance Adaboost Classifier #100DaysOfML #MachineLearning #DataScience #GSoC2026

14

Days 83-90: Ensemble Learning Techniques Completed videos 83-90 from @CampusX_official Decision Tree visualization Ensemble Learning Voting methods Hard & Soft Voting Bagging techniques Bagging Classifiers & Regressors #100DaysOfML #MachineLearning #DataScience #GSoC2026

18

Days 74-80: Classification & Decision Trees Completed videos 74-80 from @CampusX_official Gradient Descent Confusion Matrix Precision, Recall, F1 Softmax Regression Polynomial features Hyperparameters Decision Trees #100DaysOfML #MachineLearning #DataScience #GSoC2026

17

Days 70-80: Regularization & Logistic Regression Completed videos 66-72 from @CampusX_official Lasso & ElasticNet Regression Logistic Regression basics Perceptron Trick Sigmoid Function Loss functions #100DaysOfML #MachineLearning #DataScience #GSoC2026

17

Days 60-70: Gradient Descent & Advanced Regression Completed videos 56-62 from @CampusX_official Gradient Descent variants Batch & Stochastic methods Polynomial Regression Bias-Variance Trade-off Ridge Regression #100DaysOfML #MachineLearning #DataScience #GSoC2026

16

Days 50-60: PCA & Linear Regression Completed videos 49-55 from @CampusX_official PCA visualization Simple Linear Regression Mathematical formulation Regression metrics (MSE, MAE, R2) Multiple Linear Regression #100DaysOfML #MachineLearning #DataScience #GSoC2026

13

Days 40-50: Outlier Detection & Feature Engineering Completed videos 40-46 from @CampusX_official MICE Algorithm Outlier detection methods Z-score & IQR Winsorization Feature Construction Curse of Dimensionality #100DaysOfML #MachineLearning #DataScience #GSoC2026

14

Days 30-40: Advanced Feature Engineering & Data Handling Completed videos 31-40 from @CampusX_official Power Transformations Binning & Binarization Mixed Variables DateTime features Missing Data Imputation #100DaysOfML #MachineLearning #DataScience #GSoC2026

16

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