May 26
Day 15 of #100DaysOfDataScience
Started learning Statistics today.
The deeper I go into Data Science,
the more I realize:
Machine Learning is mostly about understanding data properly.
Covered:
Variance
Standard Deviation
Z-Score
Probability
Outliers
Strong fundamentals first.
1
4
116
May 22
Day14 #100DaysOfDataScience ๐
13 days of consistency.
Learned:
โขPython,NumPy,Pandas
โขMatplotlib,Seaborn,Plotly
โขEDA & Data Visualization
โขBuilt IPL & Netflix projects
โขStarted my first Data Science internship
Next:
Statistics
MachineLearning
Consistency > Motivation.
1
108
Apr 20
Day 99/100
Applied data visualization on real datasets today
Bringing everything together, models, DAX & dashboards
Data - insights - decisions
#100DaysOfDataScience #PowerBI #DataAnalytics
3
37
Apr 17
Day 96/100
Continued DAX today
Worked on mathematical calculations & core operations
Turning numbers into insights
#100DaysOfDataScience #PowerBI #DAX
2
42
Day 88/100
Worked with Date & Time in Power BI ๐
Extracted day, week, quarter & explored fuzzy matching
Time-based data unlocks deeper insights ๐
#100DaysOfDataScience #PowerBI #DataAnalytics
1
4
26
Apr 8
Day 25 of #100DaysOfDataScience ๐
Student Performance Analysis using K-Means
Data preprocessing & feature selection
Feature scaling
Applied K-Means clustering
Identified 3 groups: Struggling, Average & Top Performers
Cluster analysis & insights
#DataScience #MachineLearning #AI
2
4
109
Apr 7
Day 24 of #100DaysOfDataScience ๐
Started Diabetes Prediction using Logistic Regression ๐ฉบ
Data cleaning & preprocessing
Feature scaling
Model training & evaluation
Saved model using joblib
#DataScience #MachineLearning #Python #LogisticRegression #AI
1
6
132
Day 80/100
Milestone Day, 20 days to go๐๐
Started data transformation in Power BI
Clean data = better insights
Power Query is powerful โก
#100DaysOfDataScience #PowerBI #DataAnalytics
3
18
Mar 28
Day 20 of #100DaysOfDataScience ๐
Built Complete Logistic Regression model on Titanic dataset ๐ข
Model training & prediction
Saved & loaded model using joblib
Evaluated using accuracy & confusion matrix
#DataScience #MachineLearning #Python #LogisticRegression #AI
3
74
Mar 27
Day 75/100
Started Power BI today ๐
Moving from SQL to data visualization & dashboards.
New phase, same consistency ๐ช
#100DaysOfDataScience #PowerBI #DataAnalytics
3
20
Mar 26
Day 19 of #100DaysOfDataScience ๐
Started Titanic Survival Prediction using Logistic Regression ๐ข
Data preprocessing
Handled missing values
Preparing dataset for model
#DataScience #MachineLearning #Python #LogisticRegression
4
103
Mar 24
Day 18 of #100DaysOfDataScience ๐
Visualized Linear Regression model performance ๐
Check out the code execution and output in the video ๐
#DataScience #MachineLearning #Python #LinearRegression #AI #CodingJourney
GitHub : github.com/datasci-shreya/Pyโฆ
1
1
12
294
Mar 24
Day 18 of #100DaysOfDataScience ๐
Analyzed Linear Regression model performance ๐
Checked feature coefficients
Compared actual vs predicted values
Visualized results using scatter plot
#DataScience #MachineLearning #Python #LinearRegression #AI
1
6
146
Mar 24
Day 71/100
Focused on INNER JOIN today.
Learned how to combine tables and return only matching records.
Getting better at working with relational data.
#100DaysOfDataScience #SQL #DataAnalytics
2
14
Mar 22
Day 16 of #100DaysOfDataScience ๐
Worked on an Advertising dataset and built a Linear Regression model to predict sales. ๐
Cleaned dataset
Checked missing values
Analyzed statistical summary
Explored correlation between features
#DataScience #ML #Python #LinearRegression
5
53
Mar 19
Day 67/100
Practiced SQL multi-table queries using the Ecommerce dataset.
Goal: Get customer info, Count total orders & Calculate total amount.
Used: LEFT JOIN, COUNT & SUM, Arithmetic operations, GROUP BY & ORDER BY
Turning raw data into insights.
#100DaysOfDataScience #SQL
2
10
Mar 18
Day 66/100
Practiced SQL joins across multiple tables.
Goal:
- Get order details
- Add product name
- Add category name
Used LEFT JOIN to connect order_details, products and categories.
Learning how to structure multi-table queries well.
#100DaysOfDataScience #SQL #DataAnalytics
2
13
Mar 12
Day 60/100
Continued practicing SQL single-table queries using the Ecommerce dataset.
Today I worked with: HAVING clause, CASE with single conditions, CASE with multiple conditions.
Learning how to do better filtering to SQL queries.
#100DaysOfDataScience #SQL #DataAnalytics
1
3
23
Day 53/100 โ SQL: Querying Single Tables
Today I learned how to query data from a single table in SQL.
Focused on:
โข Retrieving specific columns
โข Filtering data
โข Understanding table structure
Building a stronger SQL foundation.
#100DaysOfDataScience #SQL #DataAnalytics
2
14
Day 50/100 โ Introduction to SQL
Major Milestone๐๐
Today was just theory.
Focused on:
โข What SQL is
โข How databases work
โข Core commands
โข Why SQL matters in data
Halfway through the challenge.
Consistency > Motivation.
#100DaysOfDataScience #SQL
2
15