From Data Analyst to Data Scientist... The Essential Role of Basic Statistics
Sakshi Jain
Data Analyst | Transitioning to Data Science | A/B Testing & Statistical Analysis Expert | Passionate About Data-Driven Insights
About a year ago, I thought I could just jump straight into building machine learning models—because who needs stats when you have fancy algorithms, right? Wrong. After countless hours of debugging, questioning why my models were occasionally accurate (or maybe just lucky?), I sought some guidance from my mentor. She told me, ‘Before you master machine learning, you need to master statistics.’
At first, I wasn’t sure what that really meant. But after diving into basic statistics- mean, median, mode, standard deviation and correlation- ?it opened my eyes to how much that actually helps! Thank you, mentor, for this sage advice. ??
Now, armed with my statistical superpower, I can quickly understand my data—what features need more attention, which ones might already be good to go, and why certain algorithms behave like a toddler trying to decide between cookies and a nap.
Series overview
I’m excited to take you on a journey from statistics to machine learning. In this weekly series, we'll dive into three popular datasets in data science:
?? Iris Dataset
?? Titanic Dataset
?? House Price Dataset
Each week, we’ll explore key aspects such as:
?? Feature Importance
?? Feature Transformation
?? Model Selection
?? Feature Selection
?? Hyperparameter Tuning
?? Model Evaluation
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We'll work with traditional machine learning algorithms like:
?? Decision Tree
?? SVM
??♂? K-Nearest Neighbors (K-NN)
?? Random Forest
?? Na?ve Bayes
?? PCA
For each dataset, I’ll calculate basic statistics like mean, mode, median, and standard deviation, and share my assumptions on how these metrics influence the machine learning process.
Conclusion
Next week, we’ll kick off with the Iris dataset—get ready to meet some flowers and explore how basic statistics can help us make sense of them. But before we dive into Iris, I’d love to hear from you:
How do you use basic statistics in your machine learning projects? Do you start with calculating the mean, mode, and median, or do you have your own secret recipe for success? Share your thoughts in the comments below!
Let’s see how we all bloom with our different approaches. ??
#DataScience #MachineLearning #Statistics #DataAnalysis #FeatureSelection #DataScienceJourney #BasicStatistics