Name: Recurrent Neural Networks with Python
Rating: 5 (1 reviews)

What you will learn

Understanding RNN architecture and types

Implementing a basic RNN from scratch

Exploring advanced RNN variants like LSTM

Handling vanishing and exploding gradients

Applying LSTM and GRU in practical scenarios

Forecasting time series data with RNNs

Preprocessing and loading time series data

Building sentiment analysis models with RNNs

Encoding text data for NLP tasks

Course content

Master Recurrent neural networks and their advanced variants like LSTMs and GRUs using PyTorch. Gain hands-on experience processing sequential data for practical applications. Apply these pow…

Covers the limitations of traditional neural networks for sequential data and introduces the fundamentals of Recurrent Neural Networks. Explains RNN architecture, types, and step-by-step implementation through basic examples and a coding challenge.

Explores common training challenges such as vanishing and exploding gradients. Introduces advanced RNN variants including LSTM and GRU, highlighting their internal mechanisms and use cases, with practical implementation examples for each.

Focuses on processing and forecasting time series data using RNN-based models. Includes data loading, preprocessing techniques, model training, and performance evaluation, with emphasis on comparing LSTM and GRU architectures.

Demonstrates the application of RNNs to text classification tasks. Covers core NLP concepts, text encoding methods, data preparation steps, and construction of an LSTM-based model for sentiment prediction.

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Conditional Statements in Python

Explore the nuances of the conditional if-else operator in Python through clear explanations and practical examples. Strengthen your understanding with hands-on tasks that reinforce each concept, and discover how to use if-elif-else statements effectively for more complex decision-making.

Introduction to Python

Python is a high-level, interpreted, general-purpose programming language. Distinguished from languages such as HTML, CSS, and JavaScript, which are mainly utilized in web development, Python boasts versatility across multiple domains, including software development, data science, and back-end development. This course will guide you through Python's fundamental concepts, equipping you with the skills to create your own functions by the conclusion of the program.

Python Ninja

Welcome to the Python Ninja Course! This engaging and interactive course is designed to introduce you to the fundamentals of Python programming through a fun and educational game. You'll guide a ninja through various challenges, using Python to control movements and interact with objects like sushi. Starting with the basics, you'll learn how to navigate the map, pick up and place sushi, and gradually progress to more complex programming concepts such as functions, loops, and conditional statements. Each chapter offers hands-on practice to reinforce your learning, culminating in exciting challenges that test your skills. Whether you're a complete beginner or looking to sharpen your coding abilities, this course provides a comprehensive and enjoyable learning experience. Join us and become a coding ninja!

Data Types in Python

Gain a solid understanding of Python's core data types and learn how to work with them effectively. Explore numbers, booleans, and strings through hands-on exercises and practical examples. Build confidence in performing basic operations and develop the foundational skills needed to write clean and efficient Python code.

Python Data Structures

Explore the fundamental data structures of the Python programming language, including lists, dictionaries, tuples, and sets, and learn how to apply them effectively to solve real-world programming challenges.

Introduction to Pandas

Pandas is an extremely user-friendly library for data analysis. It's also designed to handle large datasets, using data structures like DataFrame and Series. This makes it an invaluable tool for Data Science. In this guide, you'll get acquainted with a range of statistical functions, including how to find correlations, modes, medians, and maximum and minimum values within a dataset. You'll also learn how to handle missing values and manipulate specific values, as well as how to remove them.

Python Loops Tutorial

Build confidence in mastering Python loops! Start with the basics of for and while loops and progress to advanced concepts like nested loops, control statements, and dynamic conditions. With hands-on practice and real-world examples, gain the skills to write efficient, clean, and powerful code. Perfect for beginners and anyone looking to sharpen their Python expertise!

Conditional Statements in Python

Explore the nuances of the conditional if-else operator in Python through clear explanations and practical examples. Strengthen your understanding with hands-on tasks that reinforce each concept, and discover how to use if-elif-else statements effectively for more complex decision-making.

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Recurrent Neural Networks with Python

Course for Intermediate Level

What you will learn

Course content

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Recurrent Neural Networks with Python

Course for Intermediate Level

What you will learn

Course content

Your subscription also includes:

Why People Choose Codefinity

Step-by-Step to Stellar Results

Trusted by Employees of Leading Companies and Students from Top Universities

Instantly access 200+ courses

Full catalog access

Try Codefinity with confidence – 30-day money-back guarantee included

Frequently Asked Questions

Still have questions?

Trusted by Employees of Leading Companies
and Students from Top Universities