• No products in the cart.

ratings 

Introduction to AI, Machine Learning & Deep Learning Essentials is an engaging, hands-on training program designed. Fast-growing, critical technologies are currently shaping the future of IT, development, and analytics.

PRIVATE
Course Access

Unlimited Duration

Last Updated

March 4, 2021

Students Enrolled

Total Reviews

Posted by
Certification

In this course you learn about:

· The What and Why of AI, Machine Learning & Deep Learning – why is this important and exciting?

· Getting the Basics: High-level skills, vocabulary and terminology

· AI, Machine Learning and Deep Learning – what are the differences and uses?

· Latest trends and research

· Who’s Using It and to What Advantage?

· How to adopt AI, ML and DL

· Hands-on Machine Learning – algorithms, neural networks, natural language processing & more

· Tools and Languages: Python, R, Spark, TensorFlow, Keras

· Deep Learning Essentials

Course Curriculum

    • What is Data Science? 00:00:00
    • New Ways of Thinking about and using Data 00:00:00
    • Challenges of processing 00:00:00
    • Technologies 00:00:00
    • Strategies 00:00:00
    • Where does data science fit in? 00:00:00
    • DS ecosystem – AI, Machine Learning, Deep Learning 00:00:00
    • Data and the Scientific Method 00:00:00
    • Data Science vs. Data Engineering 00:00:00
    • Sharing Results with Colleagues 00:00:00
    • Recording experiments 00:00:00
    • The Data Science Team members 00:00:00
    • Data Science Infrastructure 00:00:00
    • Current Tools, Trends & Technologies 00:00:00
    • Applying Data Science to Your Industry 00:00:00
    • AI – How did we get here? 00:00:00
    • Recent advances in data, hardware 00:00:00
    • Cutting edge research and applications 00:00:00
    • Getting the basics: Core terms and vocabulary 00:00:00
    • Who is leveraging this and why 00:00:00
    • Overview of ML – what’s the difference? 00:00:00
    • Related examples of ML algorithms and applications 00:00:00
    • Surrounding tools and technologies: Python and Spark 00:00:00
    • Supervised vs. Unsupervised 00:00:00
    • Classification 00:00:00
    • Regression 00:00:00
    • Clustering 00:00:00
    • Dimensionality Regression 00:00:00
    • Ensemble Methods 00:00:00
    • What is it, and how is this different than AI and ML? 00:00:00
    • Who’s using Deep Learning and Why 00:00:00
    • Deep Learning algorithms and applications 00:00:00
    • Surrounding tools and technologies: Python, TensorFlow, Keras 00:00:00
    • Rules Systems 00:00:00
    • Feedback loops 00:00:00
    • RETE and beyond 00:00:00
    • Expert Systems in practice 00:00:00
    • Neural Networks 00:00:00
    • Recurrent Neural Networks 00:00:00
    • Long-Short Term Memory Networks 00:00:00
    • Applying Neural Networks 00:00:00
    • Language and Semantic Meaning 00:00:00
    • Bigrams, Trigrams, and n-Grams 00:00:00
    • Root stemming and branching 00:00:00
    • NLP in the world 00:00:00
    • Image processing and Identification 00:00:00
    • Facial Analysis 00:00:00
    • Audio Processing 00:00:00
    • Analyzing Streaming Video 00:00:00
    • Real-world AV processing 00:00:00
    • Sentiment: The beginnings of emotional understanding 00:00:00
    • Sentiment indicators 00:00:00
    • Sentiment Sampling 00:00:00
    • Algorithmic Trading on Sentiment 00:00:00
    • Predicting Elections 00:00:00

    Course Reviews

    Profile Photo
    ashar hafeez
    0
    61

    Students

    About Instructor

    Pak

    Course Events

    [wplms_eventon_events]

    More Courses by Insturctor

    © 2021 Ernesto.  All rights reserved.  
    X