yashprakash13

import uvicorn
from fastapi import FastAPI
from model import SentimentModel, SentimentQueryModel

app = FastAPI()
model = SentimentModel()

@app.post('/predict')
def predict(data: SentimentQueryModel):
    data = data.dict()

ih2502mk

Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

jamescalam

from flask import Flask
from flask_restful import Resource, Api, reqparse
import pandas as pd
import ast

app = Flask(__name__)
api = Api(app)

class Users(Resource):
    def get(self):

sureshgorakala

Mengyuz

import numpy
import pandas
import statsmodels.api as sm

def custom_heuristic(file_path):
    '''
    You are given a list of Titantic passengers and their associated
    information. More information about the data can be seen at the link below:
    http://www.kaggle.com/c/titanic-gettingStarted/data