AI Based Projects Using Python


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Machine learning frameworks like TensorFlow, PyTorch, or scikit-learn, along with libraries for data manipulation and visualization such as Pandas and Matplotlib we use in generating AI projects. From matlabsimulation.com PhD and MS scholars can get a lot of ideas for projects involving artificial intelligence that is written in Python. Python technique are well-known, here we discuss several ideas for projects involving artificial intelligence in Python.

Here are some of the project ideas with a brief outline of how one could approach them with Python code:

Sentiment Analysis

              Natural Language Toolkit (nltk), scikit-learn can be used to categorize the sentiment of a given text as positive, negative, or neutral. A sample of the code work is given.


from sklearn.feature_extraction.text import CountVectorizer

from sklearn.naive_bayes import MultinomialNB

from sklearn.model_selection import train_test_split

# Your text data and labels

text_data = [“I love this!”, “I hate this!”, “It’s okay.”]

labels = [1, 0, 2]

# Feature extraction

vectorizer = CountVectorizer()

X = vectorizer.fit_transform(text_data)

# Split data

X_train, X_test, y_train, y_test = train_test_split(X, labels, test_size=0.2)

# Model training

clf = MultinomialNB()

clf.fit(X_train, y_train)

# Prediction

y_pred = clf.predict(X_test)

Object Detection

  We can detect and classify objects within images by using TensorFlow, OpenCV.


import tensorflow as tf

import cv2

# Load a pre-trained model

model = tf.saved_model.load(“ssd_mobilenet_v2_coco/saved_model”)

# Read image

image = cv2.imread(‘image.jpg’)

# Perform inference

# …


A simple conversational agent is built here the libraries needed are ChatterBot aa example of code is shown.


from chatterbot import ChatBot

from chatterbot.trainers import ListTrainer

chatbot = ChatBot(‘MyBot’)

trainer = ListTrainer(chatbot)

# Train the chatbot




    ‘How are you?’,

    ‘I am fine.’


# Get a response

response = chatbot.get_response(‘Hello’)

Stock Price Prediction

 We can predict future stock prices based on historical data by using Pandas, scikit-learn libraries.


import pandas as pd

from sklearn.linear_model import LinearRegression

# Load data

data = pd.read_csv(‘stock_prices.csv’)

# Data preprocessing

# …

# Model training

model = LinearRegression()

model.fit(X_train, y_train)

# Prediction

y_pred = model.predict(X_test)

Image Classification

Here images can be classified into various categories by using TensorFlow, Keras libraries.


from tensorflow.keras.models import Sequential

from tensorflow.keras.layers import Dense, Conv2D, Flatten

# Create the model

model = Sequential()

# Add layers

model.add(Conv2D(64, kernel_size=3, activation=’relu’, input_shape=(28,28,1)))

model.add(Conv2D(32, kernel_size=3, activation=’relu’))


model.add(Dense(10, activation=’softmax’))

# Compile the model

model.compile(optimizer=’adam’, loss=’categorical_crossentropy’, metrics=[‘accuracy’])

# Fit the model

model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=3)

             The above presented are just some reference coding, our research team add more features, by optimizing the model or mixing them into algorithms, techniques,functions  and frame out effectively. While we add additional preprocessing, error handling, and fine-tuning for its better outcome.

AI based Topics using PYTHON

Python Artificial intelligence project Ideas 

Python Artificial intelligence project Ideas are shared by our leading development team. Novel ideas with new tools and technologies will be assisted for scholar’s python project.

Here are a few projects on artificial intelligence in the field python, the most exciting artificial intelligence project ideas are discussed below…

  1. Voice Analysis Framework for Asthma-COVID-19 Early Diagnosis and Prediction: AI-based Mobile Cloud Computing Application
  2. AI-Based Online P2P Lending Risk Assessment on Social Network Data with Missing Value
  3. The Role of AI Chatbots in Mental Health Related Public Services in a (Post)Pandemic World: A Review and Future Research Agenda
  4. Cyber Security and Securing Subjective Patient Quality Engagements in Medical Applications: AI and Vulnerabilities
  5. An AI based solution for the control of 3D real-time sensor-based gaming
  6. Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era
  7. Robust AI-enabled Simulation of Treatment Paths with Markov Decision Process for Breast Cancer Patients
  8. Revitalizing Traditional Health Practices with Healing Hands: An AI powered Chatbot
  9. Analysis And Implementation of a Novel AI-Based Hybrid Model for Detecting, Predicting and Identification Of COVID-19 Spread
  10. A study on the applicability of AI in Pharmaceutical Industry
  11. A Comprehensive Review of the Negative Impact of Integration of AI in Social-Media in Mental Health of Users
  12. Traffic Safety in Future Cities by Using a Safety Approach Based on AI and Wireless Communications
  13. A Deep Reinforcement Learning Agent for General Video Game AI Framework Games
  14. Analytical study on use of AI techniques in tourism sector for smarter customer experience management
  15. Artificial intelligence techniques: an introduction to their use for modelling environmental systems
  16. Explainability for artificial intelligence in healthcare: a multidisciplinary perspective
  17. Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges
  18. Artificial intelligence to deep learning: machine intelligence approach for drug discovery
  19. The impact of artificial intelligence in medicine on the future role of the physician
  20. A survey on explainable artificial intelligence (xai): Toward medical xai

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