Nostr Web Client

Thomas Hall 6mo ago

There’s more to life than Bitcoin and blockchain ..

Just did a full detail and graphene coat on the new R9

#yzfr9 #staksats

Thomas Hall 6mo ago

Not exactly how I like to end my day…..

Thomas Hall 6mo ago

Just completed another predictive analytics project using AI and Machine Learning to predict banking customer churn.

Skills:

Project Overview:

Using anonymized bank customer data—including features like credit score, tenure, balance, products held, and activity status—this project built a binary classification model to predict churn likelihood.

Objective

✅ Identify customers at high risk of churn (binary classification)

✅ Prioritize Recall to reduce false negatives (missed churners)

✅ Balance the dataset using SMOTE to handle class imbalance

✅ Compare optimizer effectiveness (SGD vs. Adam)

✅ Evaluate model robustness with and without Dropout regularization

Key Analytical Approaches:

Data Cleaning & Preprocessing → Checked for nulls, converted categorical features via one-hot encoding, normalized features, and split into train/validation/test.

Exploratory Data Analysis (EDA) → Analyzed churn patterns across customer demographics.

Class Imbalance Correction → Applied SMOTE (Synthetic Minority Over-sampling Technique) to improve minority class representation.

Model Development → Trained and compared: • Neural Network with SGD Optimizer • Neural Network with Adam Optimizer • Neural Network with Dropout Regularization • Neural Network with SMOTE-enhanced training

Evaluation Metrics → Focused on Recall, AUC, F1-Score, and Confusion Matrix.

Hyperparameter Tuning → Experimented with layer sizes, learning rates, optimizers, batch sizes, and epochs to optimize performance.

Results & Business Impact:

✅ Final model (NN with Adam, SMOTE, and Dropout) achieved Recall: 0.80 and AUC: 0.83 on the test set

✅ Significant improvement in detecting churners vs. baseline models

✅ Model prioritizes capturing as many at-risk customers as possible for proactive outreach

✅ Confusion matrix and ROC curves validate robust generalization to unseen data

Tools & Techniques Used:

✅ Python → Core implementation language

✅ Google Colab → Notebook-based development environment

✅ NumPy, pandas → Data wrangling and manipulation

✅ Matplotlib, Seaborn → Visualizations

✅ Scikit-learn → Model evaluation and metrics

✅ TensorFlow / Keras → Neural network development

✅ SMOTE (imblearn) → Synthetic resampling to correct imbalance

Business & Problem-Solving Skills Demonstrated:

✅ Churn Risk Modeling → Built a risk prediction framework tailored to customer retention

✅ Strategic Metric Selection → Prioritized Recall to avoid losing valuable customers

✅ Deep Learning Proficiency → Deployed tuned neural networks with dropout for generalization

✅ Model Interpretability → Delivered confusion matrices and ROC curves for stakeholder review

Project Portfolio Page:

https://datascienceportfol.io/ThomasHall/projects/6

#AI #MachineLearning #PredictiveAnalytics

Thomas Hall 6mo ago 💬 1

Sweet - just received my new @Gemini MC - 🤑

#btc go up 🚀

Thomas Hall 6mo ago

Just HODL

#btc going higher

Thomas Hall 6mo ago

Happy Fathers Day - just got back from an awesome trip with the family in Hi.

#hawaii #waikiki #bitcoinfixesthat

Thomas Hall 6mo ago

This is a nice day / #BTC go up

Thomas Hall 7mo ago

👀 Reflections from Bitcoin 2025 in Las Vegas!

What an awesome event... I had the chance to attend last week’s Bitcoina 2025 conference where I met a ton of great people; from industry insiders, to YouTubers, to corporate execs looking to implement Bitcoin and blockchain payment solutions for their own organization.

Shout out to Dan Edwards, Chief Operations Officer at Steak 'n Shake for his keynote and for blazing the trail forward for others to follow.

If you missed the event, one thing was clear; stablecoins stole the show.

Over 35,000 attendees gathered to discuss the future of crypto, and while Bitcoin was the headliner, the real energy was around USD-pegged stablecoins—and their growing importance in both U.S. policy and global finance.

One of the most notable moments? Vice President JD Vance’s keynote, where he voiced strong support from the current administration for building out a regulatory framework that supports stablecoin innovation. His push for the GENIUS Act—which would establish clear guidelines for fully-backed stablecoins—highlighted how central these assets are becoming in the broader economic strategy to maintain U.S. dollar dominance globally.

🧾 Other highlights:

· Senator Cynthia Lummis spoke about bipartisan momentum to pass the GENIUS Act as the first major U.S. digital asset legislation.

· Tether announced expansion plans, while big institutions teased their own stablecoin projects.

· Policy leaders emphasized stablecoins as a way to modernize payment infrastructure and attract global capital into U.S. financial markets.

💡 The big picture? Stablecoins are moving from speculative tools to strategic instruments. As digital assets continue to mature, they're increasingly being seen as critical infrastructure—not just innovation.

Watching how the GENIUS Act progresses will be key. It could set the tone for how the U.S. regulates and champions digital currency adoption going forward.

Curious to hear your thoughts—especially from those building in the space.

Were you there? What stood out to you?

#Bitcoin2025 #Stablecoins #Web3 #CryptoPolicy #Fintech #GENIUSAct #DigitalDollar #BlockchainLeadership