Learn Artificial intelligence using Python eBook
Artificial intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and act like humans. These machines can be trained to perform tasks such as recognizing patterns, learning from data, and making decisions.
Machine learning is a subset of AI that involves the use of algorithms and statistical models to enable computers to learn from data and improve their performance on a specific task without being explicitly programmed. In other words, machine learning algorithms can learn from the data they are given, rather than being explicitly told how to perform a task.
The eBook is in PDF format and is priced at $9.99
Please click here to buy the book.
The book covers the folowing:
[1] Introduction to AI and machine learning:
Define artificial intelligence and machine learning
Explain the difference between AI and machine learning
Discuss the various applications of AI and machine learning
Introduce Python as a programming language for AI and machine learning
[2] Setting up a Python development environment:
Install Python and necessary libraries and tools
Set up an integrated development environment (IDE)
Familiarization with Python syntax and data types
[3] Exploring and preprocessing data:
Load and explore data sets using Python libraries such as Pandas
Clean and preprocess data using techniques such as missing value imputation and normalization
[4] Building and evaluating machine learning models:
Supervised learning algorithms such as linear regression and support vector machines
Unsupervised learning algorithms such as k-means clustering and principal component analysis
How to evaluate the performance of machine learning models using metrics such as accuracy and mean squared error
[5] Deep learning with neural networks:
Neural networks and deep learning
Build and train neural networks using Python libraries such as TensorFlow and Keras
Techniques for improving the performance of neural networks, such as regularization and model ensembles
[6] Natural language processing:
Introduction to natural language processing (NLP)
Use Python libraries such as NLTK and spaCy to perform tasks such as tokenization, stemming, and part-of-speech tagging
Build and evaluate NLP models for tasks such as language translation and sentiment analysis
[7] Applications of AI and machine learning:
Real-world applications of AI and machine learning in industries such as healthcare, finance, and marketing
The eBook is in PDF format and is priced at $9.99
Please click here to buy the book.
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