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cosmetics

Cosmetics, chemicals ... it's complicated Whenever I want to try a new cosmetic item, it's so difficult to choose. It's actually more than difficult. It's sometimes scary because new items that I've never tried end up giving me skin trouble. We know the information we need is on the back of each product, but it's really hard to interpret those ingredient lists unless you're a chemist. You may be able to relate to this situation. So instead of buying and hoping for the best, why don't we use data science to help us predict which products may be good fits for us? In this notebook, we are going to create a content-based recommendation system where the 'content' will be the chemical components of cosmetics. Specifically, we will process ingredient lists for 1472 cosmetics on Sephora via word embedding, then visualize ingredient similarity using a machine learning method called t-SNE and an interactive visualization library called Bokeh. Let's inspect our data first.

eda_sales_dataset

Utilizing data analysis on the Retail dataset, we have gained valuable insights into Sales trends, enabling us to formulate data-driven policies for future improvements in stores and warehouses. The project's next phase involves selecting additional datasets to identify new use cases and visualizing them for comprehensive analysis

predictive-analysis-of-machine

Predictive maintanence Predictive maintanence is the maintanence of machines at a predicted future time before the machine failure. This allows scheduled maintanence of the machines, reducing the unplanned downtime costs. In this notebook, we will build a deployable end-to-end classification model to predict whether a machine failure will occur or not. We will train state-of-the-art and compare their performances.

pune-muncipal-nearest-bus-stop-disatance

time_series

Developed and operationalized an accurate foreign exchange reserves forecasting model using ARIMA and Auto Regressive techniques, enabling reliable future predictions for financial planning and strategic decision-making.