Ammar Afzal

21/08/2025

🚀 𝐓𝐚𝐬𝐤 𝟏 𝐂𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝 – 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐈𝐧𝐭𝐞𝐫𝐧𝐬𝐡𝐢𝐩

As part of my internship, I worked on 𝐄𝐱𝐩𝐥𝐨𝐫𝐚𝐭𝐨𝐫𝐲 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 (𝐄𝐃𝐀) using the classic Titanic dataset from Kaggle. This task helped me practice the fundamentals of 𝐝𝐚𝐭𝐚 𝐜𝐥𝐞𝐚𝐧𝐢𝐧𝐠 🧹, 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 🔄, 𝐚𝐧𝐝 𝐯𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 📊 in Python.

🔎 𝐊𝐞𝐲 𝐒𝐭𝐞𝐩𝐬 𝐈 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐞𝐝
✨ Cleaned missing values (Age, Cabin, Embarked) and converted categorical types
📑 Generated descriptive statistics and group-based insights (e.g., survival by gender and passenger class)
📉 Visualized patterns and correlations using 𝐒𝐞𝐚𝐛𝐨𝐫𝐧 and 𝐌𝐚𝐭𝐩𝐥𝐨𝐭𝐥𝐢𝐛

🎁 Bonus: Created bar plots and heatmaps to clearly show survival rates across different groups

⚙️ 𝐓𝐨𝐨𝐥𝐬 & 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬
🐍 Python
📊 Pandas
🎨 Seaborn / Matplotlib

📊 𝐊𝐞𝐲 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬
👩‍🦰 Female passengers had a much higher survival rate than male passengers
🏛️ First-class passengers had significantly better survival chances compared to third-class
👨‍👩‍👧 Family size and embarkation port also influenced survival probability

📂 𝐆𝐢𝐭𝐇𝐮𝐛 𝐑𝐞𝐩𝐨𝐬𝐢𝐭𝐨𝐫𝐲
👉 https://github.com/iammarafzal/eda-titanic-dataset.git

This task not only improved my EDA skills but also gave me hands-on experience in presenting data-driven insights effectively.

🔥 Excited to move forward to the next tasks and continue growing in my 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐈𝐧𝐭𝐞𝐫𝐧𝐬𝐡𝐢𝐩 at Elevvo Pathways! 🚀

06/08/2025

📚 𝐃𝐚𝐲 𝟐 𝐨𝐟 𝐌𝐲 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 🚀
Today, I explored the 𝐭𝐲𝐩𝐞𝐬 𝐨𝐟 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 and their real-world use cases! Here's what I learned:

🔹 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
• Regression
• Classification
(Data with labels 📊)

🔹 𝐔𝐧𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
• Clustering
• Dimensionality Reduction
• Anomaly Detection
• Association Rule Learning
(Data without labels 🧩)

🔹 𝐒𝐞𝐦𝐢-𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
(A mix of labeled and unlabeled data ⚖️)

🔹 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
(Learning by interacting with the environment 🎮)

🔍 Also got familiar with 𝐝𝐚𝐭𝐚 𝐭𝐲𝐩𝐞𝐬:
• Numerical (e.g., age, salary)
• Categorical (e.g., gender, country)

Every concept is a step closer to building smart systems.
Stay tuned for more tomorrow! 💡

05/08/2025

Machine Learning isn’t magic, it’s just math that learns!
It powers your recommendations, voice assistants, and even fraud detection.
By learning from data, it helps machines make smart decisions, just like humans.
💡 The future isn't just digital, it's intelligent.

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03/08/2025