ABDULHAMEED IDRIS ADEDAMOLA

✅ How to Switch to Java 17 on Windows (Latest & Easiest Method) This guide shows the cleanest and safest way to switch to Java 17 , even if you don’t have administrator access. 🔹 Step 1: Open Environment Variables Method A (Fast): Press Windows + R , then type: sysdm.cpl Press Enter → Go to Advanced tab → Click Environment Variables Method B (Administrator Access): Press Windows key Search: Environment Variables or sysdm.cpl Right-click on it Select Run as administrator ✔ This unlocks System variables (Edit button will no longer be greyed out) 🔹 Step 2: Confirm Java 17 Installation C:\Program Files\Microsoft\jdk-17.0.18.8-hotspot 🔹 Step 3: Set JAVA_HOME Variable Name: JAVA_HOME Variable Value: C:\Program Files\Microsoft\jdk-17.0.18.8-hotspot 🔹 Step 4: Fix PATH (Most Important) Edit Path and add: %JAVA_HOME%\bin Move it to the TOP Remove or move down: Old Java (11, 21, 25) Oracle path: C:\Program Files\Common Files\Oracle\Ja...

Fix Android App Bundle Signing Key Error (Step-by-Step Guide) 🚀 How to Fix “Android App Bundle is Signed with the Wrong Key” Error If you are uploading your Android App Bundle (.AAB) to Google Play Console and you see this error: "Your App Bundle is signed with the wrong key. Ensure that your App Bundle is signed with the correct signing key..." Don’t worry — this guide will show you exactly how to fix it step-by-step. 🔴 What Causes This Error? This error happens when: You are using a different keystore (.jks) than the one registered in Play Console Android Studio auto-generates a debug or new release key You changed devices or rebuilt your project ✅ Step 1: Generate a Correct Upload Key (.jks) Open your terminal or command prompt and run: keytool -genkeypair -v -keystore upload-key.jks -alias upload -keyalg RSA -keysize 2048 -validity 10000 During setup, you will be asked: Name (CN) Organization (O) Country code (C ...

How I Fixed Missing @mipmap/ic_launcher_background in Android Studio (Complete Guide) ✅ While working on my Android project, I encountered an issue where: @mipmap/ic_launcher_background was being referenced, but the file didn’t exist in my project. This caused confusion and potential build issues. Here’s the exact solution that worked for me. 🔍 Understanding the Issue In Android development, @mipmap/ic_launcher_background is not something you manually type or guess. It refers to a real resource file inside your project: res/mipmap/ic_launcher_background If this file is missing, your launcher icon setup is incomplete. ⚠️ What NOT to Do I initially considered selecting assets from this path: C:\Program Files\Android\Android Studio\plugins\android\resources\images\asset_studio This is incorrect ❌ These are internal Android Studio assets They are not meant for app development use Using them won’t properly fix your project ✅ The Correct Solut...

ROC Curve Analysis (Model Performance Evidence) The ROC (Receiver Operating Characteristic) curve illustrates the performance of the Decision Tree classifier in distinguishing between the two classes: Poor and Fair credit scores. Evidence of Model Performance AUC Score: 0.75 Random Classifier Baseline: A diagonal reference line representing no discrimination ability (AUC = 0.50) As shown in the ROC curve, the model’s performance curve lies consistently above the diagonal baseline, indicating that it performs significantly better than random guessing. Interpretation An AUC value of 0.75 indicates that the model has a 75% probability of ranking a randomly chosen positive instance higher than a randomly chosen negative instance. In other words, the classifier demonstrates acceptable to good discriminatory performance for a baseline Decision Tree model. Conclusion: The ROC curve confirms that the model outperforms a random classifier...

AI/ML Practical Task 3 Progress AI/ML Practical Task 3 Progress Today, I started working on Task 3 of my AI/ML practical assignment using Google Colab. The goal of this task is to improve a credit risk classification model using feature selection and evaluation techniques. Dataset Overview The dataset used is the Credit Risk Dataset , which contains various financial and behavioral features used to predict credit score classification. Initial Setup I began by loading the dataset into Google Colab and preparing the data for analysis. The features and target variables were defined as follows: Features (X): Input variables derived from the dataset Target (y): Credit_Score_Coded (classification label) The dataset was then split into training and testing sets using a 60/40 ratio . Train-Test Split X_train, X_test, y_train, y_test = train_test_split( features, target, test_size=0.4, random_state=42 ) Next Steps The next phase of the tas...

🌟 How the Hierarchy Star Reports App Was Submitted for Google Play Review 🌟 Hello everyone 👋, The Hierarchy Star Reports app has successfully been submitted for Google Play review! This guide explains exactly how it was prepared for production: Step 1: Complete Closed Testing A closed test was conducted with selected users to ensure the app was stable and all features worked as intended. Feedback was collected and applied as needed. Step 2: Prepare the Production Release In Google Play Console: Navigate to Test and release → Production Click Create new release Select the existing .aab file from the library (no changes after the closed test) Step 3: Add Release Notes Release notes were entered to inform users: <en-US> Production release — same build as closed test, no changes. </en-US> Step 4: Review and Save After confirming the app bundle and release notes, Save was clicked. A warning about a deobfuscation file appeared, but this is optio...