Hello everyone! My name is Amey Gawade, and I am thrilled to embark on this 100-Day Data Science Portfolio Challenge. I am a Google-certified Data Scientist with a master’s degree in computer science (Data Science and Analytics) from EPITA Paris. With over a decade of experience in data science, product management, data analytics, statistical analytics, and business strategy analysis and execution, I have honed my skills in leveraging advanced machine learning techniques, including Natural Language Processing (NLP) and Large Language Models (LLM).
Throughout my career, I have successfully utilized data-driven insights to inform strategic decision-making, drive revenue growth, and deliver impactful solutions in dynamic environments. I have worked on various projects, such as developing the 'DidoSEO' web app to reduce SEO analysis and reporting time by 40%, and implementing a product pricing model that resulted in a significant 20% boost in revenue.
I decided to undertake this 100-day challenge to further enhance my skills, build a comprehensive portfolio, and document my learning journey to help others in the field. Over the next 100 days, I will be working on various projects and learning different data science concepts, such as data cleaning, exploratory data analysis, supervised and unsupervised learning, natural language processing, and deep learning. I will document my progress daily and share detailed reports and insights on my blog.
The primary goal of Day-2 is to get familiarised with data manipulation, analysis and visualization Python libraries :
Pandas
NumPy
Matplotlib
Seaborn
Pandas is a powerful library for data manipulation and analysis. It provides data structures such as Series and DataFrame, which are essential for handling and analyzing structured data.
Key Features
DataFrame:
A 2-dimensional labeled data structure with columns of potentially different types.
Series:
A 1-dimensional labeled array capable of holding any data type.
! pip install pandas