Rowan Benny

1649237810

Developing Chatbots project

If you want your business to prosper, you'll have to stay on top of the latest trends. The creation of a chatbot is a lengthy procedure. However, if well planned, it can be a piece of cake. The emergence of chatbots is one of the most significant recent developments in the area of customer care. On that topic, chatbots are one of the most well-known marketing tools in use today, aiding in the development of effective communication between businesses and their customers. So, read on to learn about data science projects for final year students as well as data science projects for beginners.

When it comes to chatbot creation, the most important thing to remember is to break the process down into simple steps and follow them one by one. Chatbots are quite handy if you want to improve your customer's experience by answering their questions, reducing human workload, performing remote troubleshooting, and so on. Rather than adopting a bot development framework or another platform, why not build a basic, intelligent chatbot from the ground up using deep learning? Though bots have a wide range of applications, one of the most well-known is live chat platforms, where users ask queries and a chatbot responds appropriately. There are different types of recommendation systems of the data science projects ideas.

So, in order to make your life easier, we've provided step-by-step chatbot programming guidelines. The days of waiting (not so patiently) on hold for answers to your most pressing questions are quickly fading away. In this lesson, you'll learn how to use Keras to create an end-to-end domain-specific intelligent chatbot solution.

Overview:

A chatbot is a piece of software that can communicate and conduct tasks in the same way that a human can. Because we're going to build a deep learning model, we'll need data to train it. Chatbots are marketing and automation solutions that are supposed to assist people by interacting with them and performing human-like interactions. Chatbots are widely utilised in customer service, social media marketing, and client instant messaging.

However, because this is a rudimentary chatbot, we will neither collect nor download any significant datasets. To communicate, these bots may employ Natural Language Processing (NLP) or audio analysis techniques, making them sound more natural. Based on how they're developed, there are two primary sorts of chatbot models: retrieval-based and generation-based models. These intentions may differ from one

chatbot solution to the next depending on the domain in which you are implementing a chatbot solution. AI-Chatbots are widely recommended by entrepreneurs and organizations. Let's take this data science project step by step.

Import and load the data file

import nltk

from nltk.stem import WordNetLemmatizer

lemmatizer = WordNetLemmatizer()

import json

import pickle

import numpy as np

from keras.models import Sequential

from keras.layers import Dense, Activation, Dropout

from keras.optimizers import SGD

import random

words=[]

classes = []

documents = []

ignore_words = ['?', '!']

data_file = open('intents.json').read()

intents = json.loads(data_file)

Preprocess data 

for intent in intents['intents']:

    for pattern in intent['patterns']:

     #tokenize each word

     w = nltk.word_tokenize(pattern)

     words.extend(w)

     #add documents in the corpus

     documents.append((w, intent['tag']))

           if intent['tag'] not in classes:

         classes.append(intent['tag'])

Create training and testing data 

training = []

 

output_empty = [0] * len(classes)

 

for doc in documents:

  

    bag = []

Build the model

model = Sequential()

model.add(Dense(128, input_shape=(len(train_x[0]),), activation='relu'))

model.add(Dropout(0.5))

model.add(Dense(64, activation='relu'))

model.add(Dropout(0.5))

model.add(Dense(len(train_y[0]), activation='softmax'))

sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)

model.compile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy'])

hist = model.fit(np.array(train_x), np.array(train_y), epochs=200, batch_size=5, verbose=1)

model.save('chatbot_model.h5', hist)

print("model created"

 output_row = list(output_empty)

    output_row[classes.index(doc[1])] = 1

    training.append([bag, output_row])

random.shuffle(training)

training = np.array(training)

train_x = list(training[:,0])

train_y = list(training[:,1])

print("Training data created")

Predict the response (Graphical User Interface)

import nltk

from nltk.stem import WordNetLemmatizer

lemmatizer = WordNetLemmatizer()

import pickle

import numpy as np

from keras.models import load_model

model = load_model('chatbot_model.h5')

import json

import random

intents = json.loads(open('intents.json').read())

words = pickle.load(open('words.pkl','rb'))

def clean_up_sentence(sentence):

sentence_words = nltk.word_tokenize(sentence)

 return sentence_words

def bow(sentence, words, show_details=True):

 sentence_words = clean_up_sentence(sentence)

bag = [0]*len(words)

    for s in sentence_words:

     for i,w in enumerate(words):

         if w == s:

             bag[i] = 1

             if show_details:

                 print ("found in bag: %s" % w)

    return(np.array(bag))

def predict_class(sentence, model):

 p = bow(sentence, words,show_details=False)

    res = model.predict(np.array([p]))[0]

    ERROR_THRESHOLD = 0.25

     results.sort(key=lambda x: x[1], reverse=True)

    return_list = []

    for r in results:

        return_list.append({"intent": classes[r[0]], "probability": str(r[1])})

    return return_list

.def getResponse(ints, intents_json):

    tag = ints[0]['intent']

    list_of_intents = intents_json['intents']

    for i in list_of_intents:

     if(i['tag']== tag):

         result = random.choice(i['responses'])

         break

    return result

def chatbot_response(text):

    ints = predict_class(text, model)

    res = getResponse(ints, intents)

    return res

#Creating GUI with tkinter

import tkinter

from tkinter import *

def send():

    msg = EntryBox.get("1.0",'end-1c').strip()

    EntryBox.delete("0.0",END)

    if msg != '':

     ChatLog.config(state=NORMAL)

     ChatLog.insert(END, "You: " + msg + '\n\n')

     ChatLog.config(foreground="#442265", font=("Verdana", 12 ))

     res = chatbot_response(msg)

     ChatLog.insert(END, "Bot: " + res + '\n\n')

     ChatLog.config(state=DISABLED)

     ChatLog.yview(END)

base = Tk()

base.title("Hello")

base.geometry("400x500")

base.resizable(width=FALSE, height=FALSE)

#Create Chat window

ChatLog.config(state=DISABLED)

#Bind scrollbar to Chat window

scrollbar = Scrollbar(base, command=ChatLog.yview, cursor="heart")

ChatLog['yscrollcommand'] = scrollbar.set

#Create Button to send message

SendButton = Button(base, font=("Verdana",12,'bold'), text="Send", width="12", height=5,

                 bd=0, bg="#32de97", activebackground="#3c9d9b",fg='#ffffff',

                 command= send )

#Create the box to enter message

EntryBox = Text(base, bd=0, bg="white",width="29", height="5", font="Arial")

#EntryBox.bind("", send)

#Place all components on the screen

scrollbar.place(x=376,y=6, height=386)

ChatLog.place(x=6,y=6, height=386, width=370)

EntryBox.place(x=128, y=401, height=90, width=265)

SendButton.place(x=6, y=401, height=90)

base.mainloop()

If you want to learn more about how to do data science projects step by step, visit our website Learnbay: data science course in Chennai.

 

Keywords

Search Volume

Competition

data science project

17,480

25 (Low)

data science projects ideas

7,690

30 (Low)

data science project for final year

1,180

30(Low)

Data science project for beginners

7,500

26(Low)

data science projects step by step

2,240

31 (Low)

 

 


 

What is GEEK

Buddha Community

Best Chatbot Development Company in USA - WebClues Infotech

Best Chatbot Development Company in USA

It is believed that one of the technology among the top 5 that has the capability to change the world for the better is ChatBot. Chatbots are a new way of communication and attending to the customer at their convenience instead of the business.

Want to develop a Chabot for automating your business communication?

WebClues Infotech has the expertise and skills required for a team to develop such an important and critical system of communication for a business. Developing a Chatbot requires a huge industry experience as well as enough resources to tackle such a complex task which WebClues Infotech posses with its 120+ team members.

Want to know more bout of Chatbot development services?

Visit: https://www.webcluesinfotech.com/chatbots-development/

Share your requirements https://www.webcluesinfotech.com/contact-us/

View Portfolio https://www.webcluesinfotech.com/portfolio/

#best chatbot development company in usa #best chatbot development company #chatbot development company #chatbot development company in usa #chatbot development #ai chatbot development services

Juned Ghanchi

1621315103

Chatbot Service India, Chatbot Development Company India

We provide modernistic chatbot app development services in India and across the world. Voice bots and chatbots created by our team of developers will transform and channelize your communication process with the clients.

Using chatbot apps for business development is a trend. Our developers build apps using the latest technologies like Dialogflow, IBM Watson, Amazon Lex, fastText, Rasa NLU, & Microsoft Bot Framework.

To revolutionize the business development process, hire chatbot app developers in India.

#chatbot service india #chatbot development company india #chatbot developers india #chatbot services #chatbot development company #chatbot developers

Shawn  Durgan

Shawn Durgan

1595547778

10 Writing steps to create a good project brief - Mobile app development

Developing a mobile application can often be more challenging than it seems at first glance. Whether you’re a developer, UI designer, project lead or CEO of a mobile-based startup, writing good project briefs prior to development is pivotal. According to Tech Jury, 87% of smartphone users spend time exclusively on mobile apps, with 18-24-year-olds spending 66% of total digital time on mobile apps. Of that, 89% of the time is spent on just 18 apps depending on individual users’ preferences, making proper app planning crucial for success.

Today’s audiences know what they want and don’t want in their mobile apps, encouraging teams to carefully write their project plans before they approach development. But how do you properly write a mobile app development brief without sacrificing your vision and staying within the initial budget? Why should you do so in the first place? Let’s discuss that and more in greater detail.

Why a Good Mobile App Project Brief Matters?

Why-a-Good-Mobile-App-Project-Brief-Matters

It’s worth discussing the significance of mobile app project briefs before we tackle the writing process itself. In practice, a project brief is used as a reference tool for developers to remain focused on the client’s deliverables. Approaching the development process without written and approved documentation can lead to drastic, last-minute changes, misunderstanding, as well as a loss of resources and brand reputation.

For example, developing a mobile app that filters restaurants based on food type, such as Happy Cow, means that developers should stay focused on it. Knowing that such and such features, UI elements, and API are necessary will help team members collaborate better in order to meet certain expectations. Whether you develop an app under your brand’s banner or outsource coding and design services to would-be clients, briefs can provide you with several benefits:

  • Clarity on what your mobile app project “is” and “isn’t” early in development
  • Point of reference for developers, project leads, and clients throughout the cycle
  • Smart allocation of available time and resources based on objective development criteria
  • Streamlined project data storage for further app updates and iterations

Writing Steps to Create a Good Mobile App Project Brief

Writing-Steps-to-Create-a-Good-Mobile-App-Project-Brief

1. Establish the “You” Behind the App

Depending on how “open” your project is to the public, you will want to write a detailed section about who the developers are. Elements such as company name, address, project lead, project title, as well as contact information, should be included in this introductory segment. Regardless of whether you build an in-house app or outsource developers to a client, this section is used for easy document storage and access.

#android app #ios app #minimum viable product (mvp) #mobile app development #web development #how do you write a project design #how to write a brief #how to write a project summary #how to write project summary #program brief example #project brief #project brief example #project brief template #project proposal brief #simple project brief template

Erwin  Boyer

Erwin Boyer

1624502703

11 Of The Best Artificial Intelligence Enterprise Chatbots in 2021

Chatbots for businesses help them engage their website visitors and convert them into potential customers. The implementation of chatbots transforms the way businesses interact with their users. They can use a chatbot AI for sales, marketing, customer support, and automate many other business tasks.

The AI chatbots have revolutionized the customer service experience and enabled businesses to serve their customers in a better way. Chatbots, if created and used right, can help you take your business to all-new levels of success.

To make the best AI chatbot for your business, you need an efficient chatbot builder with various advanced features. In this post, we have listed different chatbot builders with their features, pros, and cons. Just go through the post and find the one that best fits your business needs.

chatbot for your business.

  1. Chatfuel
  2. Gupshup
  3. Appy Pie Chatbot
  4. ChatterOn
  5. MobileMonkey
  6. ActiveChat.ai
  7. Imperson
  8. SnatchBot
  9. Botsify
  10. BotCore
  11. Pandorabots

#chatbots #chatbot-development #ai-chatbot #customer-support-chatbots #power-of-chatbots #enterprise-chatbots #use-cases-of-chatbots #what-is-a-chatbot

Erwin  Boyer

Erwin Boyer

1624498185

AI Chatbots for Business: Why You Need One Now!

It’s said that Artificial Intelligence will be just as smart as humans by 2050. Experts like Ray Kurzweil have even predicted that we’ll achieve a technological singularity by 2045.

From that point on, it’s believed that AI will start inventing Nobel Prize-winning inventions every 5 minutes. Granted it’s gonna be out of our control, but hey, at least we’ll see a revolutionary breakthrough.

We may think that these claims are outlandish and ridiculous, but if someone were to tell me in the 70s that there will be self-driving cars in the future, I would’ve wanted to smoke whatever they were smoking.

But guess what, here we are in 2020, and Tesla already has their self-driving cars on the roads right now. And these were all recently developed technologies. Did you know that the first chatbot was actually launched in 1966?

Features of AI Chatbots

Why Do You Need an AI Chatbot?

Chatbots Across Various Industries

Wrapping Up

#ai-chatbot #what-is-a-chatbot #chatbot-online #chatbot #chatbot-website #facebook-chatbot #google-chatbot #best-chatbot