ISL & ESL are great recommendations for an intro/deep dive into data science from the stats perspective at the undergrad / graduate level respectively. Since you specifically mentioned predicting...
ISL & ESL are great recommendations for an intro/deep dive into data science from the stats perspective at the undergrad / graduate level respectively.
Since you specifically mentioned predicting inventory, I just wanted to also mention Rob Hyndman's Forecasting book - which is written at an MBA level and might be more directly relevant to business problems. The corresponding R package is also fantastic.
Facebook's prophet package for R and python is also quite nice for getting up and running with forecasting. There is both a quick-start and whitepaper available.
As far as common gotchas, watch out for oddities in your time dimension - February will skew low (and should!) because it's three days shorter, for example, compared to an analysis at the weekly total would look normal. Know your business cycle.
ISL & ESL are great recommendations for an intro/deep dive into data science from the stats perspective at the undergrad / graduate level respectively.
Since you specifically mentioned predicting inventory, I just wanted to also mention Rob Hyndman's Forecasting book - which is written at an MBA level and might be more directly relevant to business problems. The corresponding R package is also fantastic.
Facebook's prophet package for R and python is also quite nice for getting up and running with forecasting. There is both a quick-start and whitepaper available.
As far as common gotchas, watch out for oddities in your time dimension - February will skew low (and should!) because it's three days shorter, for example, compared to an analysis at the weekly total would look normal. Know your business cycle.