Udemy - Hands-On Introduction To Artificial Intelligence(Ai)

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[ DevCourseWeb.com ] Udemy - Hands-On Introduction To Artificial Intelligence(Ai)
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Introduction
    • 1 - What is Artificial Intelligence AI.mp4 (10.2 MB)
    • 10 - Neural Networks Perceptron.mp4 (27.7 MB)
    • 11 - What are Deep Neural Networks.mp4 (20.1 MB)
    • 12 - Feed Forward Neural Networks FFNN Structure and Forward pass.mp4 (24.4 MB)
    • 13 - Input Feed Forward Neural Networks FFNN.mp4 (8.0 MB)
    • 14 - Learning Phase Feed Forward Neural Networks FFNN.mp4 (64.6 MB)
    • 15 - Back propagation and learning step Feed Forward Neural Networks FFNN.mp4 (29.6 MB)
    • 16 - Applications and Limitations of Feed Forward Neural Networks FFNN.mp4 (4.9 MB)
    • 17 - CNN Introduction.mp4 (25.7 MB)
    • 18 - CNN Convolution and Relu Layer.mp4 (29.1 MB)
    • 19 - CNN Max Pooling Layer.mp4 (15.8 MB)
    • 2 - Mapping human functions to AI technologies.mp4 (16.3 MB)
    • 20 - CNN Example end to end.mp4 (21.6 MB)
    • 21 - Recurrent Neural Network RNN.mp4 (32.1 MB)
    • 22 - RNN Architecture.mp4 (12.3 MB)
    • 23 - Generative Adversarial Networks GAN.mp4 (22.7 MB)
    • 24 - Reinforcement Learning.mp4 (29.6 MB)
    • 25 - Transfer Learning.mp4 (31.2 MB)
    • 26 - Market Potential of AI.mp4 (23.9 MB)
    • 27 - Who will loose to AI.mp4 (59.8 MB)
    • 28 - Need for retraining and reskilling.mp4 (18.3 MB)
    • 29 - How to take advantage and benefit from AI.mp4 (31.9 MB)
    • 3 - AI Branches of Machine Learning Algorithms.mp4 (23.7 MB)
    • 4 - AI Supervised Machine Learning Algorithms and Applications.mp4 (25.4 MB)
    • 5 - AI Unsupervised Machine Learning Algorithms and Applications.mp4 (19.9 MB)
    • 6 - AI Natural Language Processing and Applications.mp4 (37.3 MB)
    • 7 - AI Computer Vision and Applications.mp4 (74.6 MB)
    • 8 - AI IOT and Applications.mp4 (62.3 MB)
    • 9 - What are Neural Networks.mp4 (12.5 MB)
    2 - IBM Watson Supervised and Unsupervised Machine Learning Models
    • 30 - Building Supervised and Unsupervised Machine learning Models using IBM Watson.mp4 (14.2 MB)
    • 31 - Approach to building machine learning Models.mp4 (40.7 MB)
    • 32 - Account Setup and Configuration.mp4 (32.0 MB)
    • 33 - Supervised Building a Binary classificationML model and Uploading Data.mp4 (12.2 MB)
    • 34 - Supervised Training and testing your model using logistic regression.mp4 (41.5 MB)
    • 35 - Supervised Building a Multi class classificationML model end to end.mp4 (51.0 MB)
    • 36 - Unsupervised Building a RegressiveML Model end to end.mp4 (36.0 MB)
    • 37 - Performance Evaluation Parameters for ML Algorithms.mp4 (20.2 MB)
    3 - Natural Language Processing NLP with IBM Watson
    • 38 - Introduction to the Section.mp4 (15.2 MB)
    • 39 - IBM Watson Text to Speech.mp4 (40.6 MB)
    • 40 - IBM Watson Speech to Text.mp4 (33.5 MB)
    • 41 - IBM Watson Semantic extraction.mp4 (68.0 MB)
    4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab
    • 42 - Introduction to the Section and the experiment sheet.mp4 (26.0 MB)
    • 43 - Building a Perceptron.mp4 (21.9 MB)
    • 44 - Building a Feed Forward Neural Network with one Hidden layer Supervised.mp4 (28.7 MB)
    • 45 - Building a Deep Feed Forward Neural Network Supervised.mp4 (46.4 MB)
    • 46 - High Level Introduction to Tensor Flow Data and Setup Unsupervised.mp4 (25.6 MB)
    • 47 - Building a Regressive Feed Forward Neural NetworkFFNN Unsupervised.mp4 (74.8 MB)
    • 48 - Building a SHALLOW Regressive Feed Forward Neural Network Unsupervised.mp4 (26.7 MB)
    • 49 - Building a DEEP Regressive FFNN Unsupervised.mp4 (32.0 MB)
    • 50 - Building a Regressive FFNN with different AdamOptimizer.mp4 (29.8 MB)
    • 51 - Building a Regressive FFNN with different learning Rates and Epochs.mp4 (71.0 MB)
    • 52 - Performance Analysis of Feed Forward Neural Networks.mp4 (41.5 MB)
    5 - Convolutional Neural Networks CNN with IBM Watson
    • 53 - Section Introduction and data.mp4 (35.3 MB)
    • 54 - CNN for MNIST Architecture Walkthrough.mp4 (7.2 MB)
    • 55 - IBM Watson Account Setup Basics.mp4 (32.0 MB)
    • 56 - CNN Setup and First Run with MNIST example Part 1.mp4 (88.2 MB)
    • 57 - CNN Setup and First Run with MNIST example Part 2.mp4 (65.3 MB)
    • 58 - CNN for MNIST with SGD.mp4 (35.9 MB)
    • 59 - Optimizing CNN for MNIST.mp4 (107.0 MB)
    • 60 - CNN for CIFAR 10.mp4 (85.1 MB)
    • 61 - Optimization options for CNN on CIFAR 10.mp4 (72.3 MB)
    • 62 - CNN Unconverging Experiments.mp4 (37.1 MB)
    6 - Recurrent Neural Network RNN with Mathworks
    • 63 - Introduction the section.mp4 (11.3 MB)
    • 64 - Japanese Vowels classification with LSTM Walk through of Mathworks example.mp4 (122.9 MB)
    • 65 - Classification of human activities with LSTM Walk through of Mathworks example.mp4 (85.5 MB)
    • Bonus Resources.txt (0.4 KB)

Description

Hands-On Introduction To Artificial Intelligence(Ai)



https://DevCourseWeb.com

Last updated 8/2019
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.37 GB | Duration: 5h 43m

Learn Basics of Machine learning, Supervised , Unsupervised, FFNN, CNN, NLP, RNN

What you'll learn
Fundamental concepts of Artificial Intelligence
Be able to identify the positive and the negative impact that AI will create
Clearly define what is AI and Deep Learning
Test Feed Forward Neural Networks(Classification and Regression) on Tensor Flow simulator and Google Colab
Test Natural Language Processing (NLP) models using IBM Watson
Build Convolutional Neural Network(CNN) on IBM Watson for MNIST and CIFAR 10 Datasets (No coding)
Build Supervised and Unsupervised Machine learning Models using IBM Watson (No coding)
Test Recurrent Neural Network (RNN) on Mathworks
Requirements
Basic knowledge of IT, Maths and Data
Description
Welcome to this exciting and eye opening course on Artificial Intelligence(Part 1) . We believe that AI will touch everybody in some level, whether you are a technical or a non technical person and also that you can excel in many roles in AI with just a functional understanding of coding.We will start from the basics , break myths, clarify your understanding as to what is this mysterious term AI, (many are surprised to know that it encompasses, Machine Learning, NLP,Computer Vision, IOT, Robotics and more). We will also understand the current state of AI and its positive and negative impact in the near future.Then we will apply the concepts we learnt with zero to little coding Involved.- Machine learning (Supervised and Unsupervised) with IBM Watson - Natural Language Processing (NLP) with IBM Watson- Feed Forward Neural Networks (FFNN) with Tensor Flow Simulator- Convolutional Neural Networks with (CNN) with IBM Watson- Recurrent Neural Networks (RNN) with Mathworks AI brings tremendous opportunity like higher economic growth, productivity and prosperity but the picture is not all rosy. lets look at some data points from the renowned Mckinsey&Company." 250 million new jobs are likely to be created by 2030"*" In the midpoint adoption scenario 400 million Jobs are likely to be lost by 2030"*" In the midpoint adoption scenario 75 million will need change occupational categories by 2030"*AI is the top priority for Companies, governments and institutions alike. AI surpasses a certain product, or vertical, or function, or a specific industry , it encompasses everything. It is all prevalent.Based on the report there will be considerable shortages in the IT sector and companies are looking to fill these gaps by retraining, hiring, redeploying, contracting and even hiring from non traditional sources. Technological skill is the TOP skill that will be required during this time and by one research they will need 250,000 data scientists by 2030. If you develop these skills and knowledge , you can take advantage of this revolution irrespective of your role, company or Industry you belong to. So if you are "AI ready then you are future ready"AI is here to stay and the ones who get on board fast and adapt to it will be in a much better position to face the exciting but uncertain future.Choose Success , make yourself invaluable and irreplaceable. I will see "YOU" on the inside.God Speed.

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Udemy - Hands-On Introduction To Artificial Intelligence(Ai)

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2.4 GB
seeders:4
leechers:11
Udemy - Hands-On Introduction To Artificial Intelligence(Ai)

Torrent hash: 2A249D1ED371DC00F2542BAF61F34AEA73949E47