My first hands on experience in EDA , machine learning algorithms , CNN and NLP

Abstract: The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit (variable y).

Bank client data:

Age (numeric)

Job : type of job (categorical: 'admin.', 'blue-collar', 'entrepreneur', 'housemaid', 'management', 'retired', 'self-employed', 'services', 'student', 'technician', 'unemployed', 'unknown')

Marital : marital status (categorical: 'divorced', 'married', 'single', 'unknown' ; note: 'divorced' means divorced or widowed) Education (categorical: 'basic.4y', 'basic.6y', 'basic.9y', 'high.school', 'illiterate', 'professional.course', 'university.degree', 'unknown')

Default: has credit in default? (categorical: 'no', 'yes', 'unknown')

Housing: has housing loan? (categorical: 'no', 'yes', 'unknown')

Loan: has personal loan? (categorical: 'no', 'yes', 'unknown')

Contact: contact communication type (categorical:'cellular','telephone')

Month: last contact month of year (categorical: 'jan', 'feb', 'mar',…, 'nov', 'dec')

Dayofweek: last contact day of the week (categorical:'mon','tue','wed','thu','fri')

Duration: last contact duration, in seconds (numeric).

Campaign: number of contacts performed during this campaign and for this client (numeric, includes last contact)

Pdays: number of days that passed by after the client was last contacted from a previous campaign (numeric; 999 means client was not previously contacted)

Previous: number of contacts performed before this campaign and for this client (numeric)

Poutcome: outcome of the previous marketing campaign (categorical: 'failure','nonexistent','success')

Emp.var.rate: employment variation rate - quarterly indicator (numeric)

Cons.price.idx: consumer price index - monthly indicator (numeric)

Cons.conf.idx: consumer confidence index - monthly indicator (numeric)

Euribor3m: euribor 3 month rate - daily indicator (numeric)

Nr.employed: number of employees - quarterly indicator (numeric) Output variable (desired target):

y - has the client subscribed a term deposit? (binary: 'yes', 'no')