Master Machine Learning & Deep Learning with 20 Python Projects
What you will learn:
- Practical application of machine learning and deep learning algorithms in real-world problems
- Implementation of various ML/DL algorithms in Python
- Proficiency in Python for ML/DL tasks
- Understanding and application of prediction models
- Data preparation, preprocessing, and visualization for ML/DL
- Working with various case studies and real-world datasets
- Utilizing APIs for data acquisition
- Employing various machine learning and deep learning libraries in Python
- Building and implementing different types of neural networks
- Image processing using Artificial Neural Networks (ANN)
- Classification with neural networks
- Natural Language Processing (NLP) techniques and applications
- Forecasting sales, prices, and other time-series data
- Using algorithm validation metrics (confusion matrix, accuracy, precision, recall, F1-score)
- Over 40 comprehensive cheat sheets on Data Science, Machine Learning, Deep Learning, and Python
Description
Unlock the power of AI! This comprehensive course goes beyond theory, equipping you with practical machine learning and deep learning skills through 20 real-world Python projects. Learn to build intelligent systems that predict stock prices, classify images, analyze sentiments, and much more.
Starting with foundational concepts, you'll dive into a curated selection of popular projects, mastering algorithms like logistic regression, Naive Bayes, and neural networks. Each project includes detailed coding instructions and implementation in Python, boosting both your AI and Python proficiency.
We cover essential techniques including data preprocessing, visualization, model validation (confusion matrices, accuracy, precision, recall, F1-score), and deploying various prediction methods. You'll explore diverse datasets across different domains, gain expertise in image processing and NLP (Natural Language Processing), and even build a recommendation system.
This course is perfect for individuals with basic machine learning and deep learning knowledge looking to build a robust portfolio. You’ll learn to leverage powerful Python libraries and analyze real-world data to solve complex problems. Furthermore, receive over 40 valuable cheat sheets covering data science, machine learning, deep learning, and Python, providing readily accessible references for your future endeavors.
Don't just learn AI, build it. Enroll today and transform your career.
Curriculum
Introduction
This introductory section lays the groundwork for the course, providing a comprehensive overview of machine learning and deep learning concepts. It sets the stage for the practical projects that follow.
Waiter Tips Prediction with Machine Learning
This section explores predicting waiter tips using machine learning techniques. You'll learn the requirements, apply a suitable machine learning model, and review the provided code for implementation.
Future Sales Prediction with Machine Learning
Here, you'll tackle the challenge of predicting future sales. The section covers requirements, applies a machine learning model for prediction, and provides the corresponding code for implementation.
Cryptocurrency Price Prediction with Machine Learning
Learn to predict cryptocurrency prices for the next 30 days. This section focuses on applying machine learning models to financial time series data, and includes the necessary code.
Stock Price Prediction with LSTM Neural Network
This section teaches you to predict stock prices using the power of LSTM neural networks. You will learn the necessary techniques and receive the corresponding code for implementation.
Image Classification with Neural Networks
This practical section demonstrates image classification using neural networks. It covers the project requirements, the implementation of the neural network model, and the provided code.
Visualize a Machine Learning Algorithm
Learn to visualize a machine learning algorithm effectively. This section covers the requirements, visualization techniques, and the code necessary for implementation.
Instagram Reach Analysis with Machine Learning
Analyze Instagram reach using machine learning. The section explains the requirements, applies machine learning models for analysis, and provides the corresponding code.
Mobile Price Classification with Machine Learning
Learn to classify mobile phone prices using machine learning models. The section details the requirements, implementation, and accompanying code.
Gold Price Prediction with Machine Learning
Predict gold prices using machine learning techniques. This section covers the implementation details and the provided code.
Language Translation with Machine Learning
Explore language translation with machine learning models. This section covers project requirements, model implementation, and the accompanying code.
Covid-19 Vaccine Sentiment Analysis
Analyze sentiment towards Covid-19 vaccines. This section covers the project requirements, sentiment analysis techniques, and the associated code.
Hotel Recommendation System with Natural Language Processing (NLP)
Build a hotel recommendation system using NLP techniques. The section describes the requirements, NLP methods used, and provides the associated code.
Email Spam Detection with Natural Language Processing (NLP)
Learn email spam detection using NLP. This section covers the requirements, implementation details, and the corresponding code.
Data Augmentation in Deep Learning and Neural Networks model
Learn the importance of data augmentation in deep learning. This section covers the techniques and their application with provided code.
Image to Pencil Sketch
Learn to convert images into pencil sketches using image processing techniques and the provided code.
Hate Speech Detection with Machine Learning
Build a hate speech detection model using machine learning. This section outlines the requirements, implementation, and associated code.
SMS Spam Detection with Machine Learning
Build a model to detect SMS spam messages using machine learning. This section covers the requirements, model building, and the accompanying code.
Resume Screening with Machine Learning
Learn to build a machine learning model for resume screening. The section covers the requirements, implementation, and provided code.
Credit Card Fraud Detection with Machine Learning
This section focuses on building a machine learning model for credit card fraud detection, covering requirements, implementation, and code.
YouTube Trending Videos Analysis
Analyze YouTube trending video data using machine learning. This section outlines requirements, implementation, and the associated code.
Cheat Sheet
Access comprehensive cheat sheets covering data science, machine learning, deep learning, and Python.
