• Vikesha T
• Roobashree S
• Pavithra P
• Dr. S. Durgadevi

Selecting the appropriate algorithm for a project can be a challenging and time-consuming task, and even a small error in the selection process can significantly impact the results. Additionally, it can be difficult for humans to compare the benefits and drawbacks of different algorithms. The primary goal of this particular project is to forecast product sales using social ads and analyze the resultant sales and profits. To achieve this prediction, we have opted to allow the machine to choose the most suitable algorithm by evaluating nine different algorithms and selecting the one that yields the best outcome.

Baseline Modelling, Machine learning, Hyper Tuning, Random Search CV, Standard Scaler.

"A BASELINE CLASSIFIER APPROACH USING SOCIAL ADS FOR SALES PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.g315-g319, May-2023, Available :http://www.jetir.org/papers/JETIR2305645.pdf

"A BASELINE CLASSIFIER APPROACH USING SOCIAL ADS FOR SALES PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppg315-g319, May-2023, Available at : http://www.jetir.org/papers/JETIR2305645.pdf