Build 3 Data Science Projects. Data analyst | Data Science | AI | Python | Pandas
In this video we embark on a journey through the realm of Machine Learning with three practical applications. Our first project delves into a dataset from Taco Bell, where we'll conduct a thorough sales analysis and customer preferences. Following that, we'll tackle an SMS filter, employing machine learning to categorize messages as either spam or 'ham' (non-spam). Finally, we culminate our projects with a predictive model for breast cancer detection.
Throughout this hands-on experience, we'll learn powerful machine learning algorithms, including linear regression, KNN, MultinomialNB, and logistic regression. Additionally, we'll explore the art of data visualization using tools like Pyplot and Seaborn. So sit back, relax, and enhance your Machine Learning skills with us!
Materials / References:
Github Codes and Datasets (give it a star ⭐):
Tacobel - https://github.com/mendsalbert/tacobells
SMS - https://github.com/mendsalbert/Spam-D...
Breast cancer - https://github.com/mendsalbert/breast...
Visual Studio website - https://code.visualstudio.com/
Python official website - https://www.python.org/
In this single video, you'll:
-Dive into a Taco Bell dataset to perform sales analysis and customer preference assessments, honing your skills in data manipulation and interpretation.-Develop an SMS classifier using machine learning to differentiate between spam and 'ham' messages, enhancing your understanding of text classification techniques.-Build a breast cancer prediction model, applying advanced machine learning algorithms like linear regression, KNN, MultinomialNB, and logistic regression to make informed predictions.
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Github: https://github.com/mendsalbert
Business inquiries:
email: albert.k.mends@gmail.com
Timestamps
00:00:00 - Intro
00:01:03 - Case 1: Tacobell Sales analysis
00:18:57 - Case 2: SMS Spam Detection
00:28:44 - Case 3: Breast cancer predictions Model
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