Logistic Regression Steps: 8 and 9

#8. Predict
model_predict = model.predict(X_test)
new_project = [
    0, #Comments
    9, #Rewards
    2500, #Goal
    157, #Backers
    31, #Duration in Days
    319, #Facebook Friends
    110, #Facebook Shares
    1, #Creator - # Projects Created
    0, #Creator - # Projects Backed
    0, ## Videos
    12, ## Images
    872, ## Words (Description)
    65, ## Words (Risks and Challenges)
    0, ## FAQs
    0, #Currency_AUD
    1, #Currency_CAD
    0, #Currency_EUR
    0, #Currency_GBP
    0, #Currency_NZD
    0, #Currency_USD
    0, #Top Category_Art
    0, #Top Category_Comics
    0, #Top Category_Crafts
    0, #Top Category_Dance
    0, #Top Category_Design
    0, #Top Category_Fashion
    1, #Top Category_Film & Video
    0, #Top Category_Food
    0, #Top Category_Games
    0, #Top Category_Journalism
    0, #Top Category_Music
    0, #Top Category_Photography
    0, #Top Category_Publishing
    0, #Top Category_Technology
    0, #Top Category_Theater
    #0, #Facebook Connected_No
    #0, #Facebook Connected_Yes
    #0, #Has Video_No
    #1, #Has Video_Yes
]
new_pred = model.predict([new_project])
print(new_pred)