Recognize Speech Commands with Deep Learning you own this product

prerequisites
intermediate Python, NumPy, pandas, Matplotlib,Tensorflow, and Keras • basics of machine learning and deep learning
skills learned
performing digital audio processing • extracting spectral features from raw audio data • building deep learning architectures for audio
Vamsi Sistla
4 weeks · 3-5 hours per week · INTERMEDIATE
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liveProject liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing. These self-paced projects also come with full liveBook access to select books for 90 days plus permanent access to other select Manning products. $34.99 $49.99 you save $15 (30%)
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Look inside
Voice assistants and speech-based applications need a reliable understanding of human commands. Deep learning systems trained on audio data are a great way for models to learn directly from sound and easily classify what humans are telling them.

In this liveProject, you’ll become a data scientist prototyping a speech command system for a medical organization. Your company’s application will allow hospital patients to adjust their room TVs with their voice, and you’ve been tasked with building the core: a machine learning pipeline that can label audio inputs with given command words. You’ll tackle preprocessing and feature engineering methods for audio signals, expand your existing machine learning capabilities with audio data, and get hands-on experience with TensorFlow, Keras, and other powerful Python deep learning tools.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Vamsi Sistla
Vamsi Sistla is a proven leader in data science and applied AI. He has experience in managing large-scale projects and teams in data engineering, ML operations, and ML modeling. He has helped in developing and implementing enterprise AI strategy. He has experience in building distributed machine learning workflows using Apache Spark, DASK, Rapids and Kubernetes. Currently, he is working at Nike, Inc. as Director of Reusable Features and ML Models. In the past he has done 2 startups, and also has a master’s in data sciences (MIDS) from the University of California, Berkeley.

prerequisites

This liveProject is for confident Python programmers with existing experience in machine learning. It will hone your skills for handling the uncommon audio data type, and constructing deep learning pipelines. To begin this liveProject, you will need to be familiar with:

TOOLS
  • Intermediate Python
  • Intermediate NumPy
  • Intermediate pandas
  • Intermediate Matplotlib
  • Intermediate TensorFlow
  • Intermediate Keras
TECHNIQUES
  • Basics of data analysis
  • Basics of supervised machine learning
  • Classification problems and suitable quality metrics
  • Supervised training of artificial neural networks

you will learn

In this liveProject, you’ll master foundational skills in audio data processing that provide an excellent starting point for voice-controlled assistants, conversational UIs, and other speech apps.

  • Audio processing with Python
  • Representing audio data
  • Feature engineering for machine learning with audio
  • Computing and visualizing spectrograms
  • Convolutional neural network architectures for audio
  • GPU-accelerated deep learning

features

Self-paced
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Project roadmap
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book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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