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

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Description
[ DevCourseWeb.com ] Hands-On Introduction To Artificial Intelligence(Ai)



If You Need More Stuff, kindly Visit and Support Us -->> 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.



Overview



If You Need More Stuff, kindly Visit and Support Us -->> https://CourseWikia.com



Get More Tutorials and Support Us -->> https://FreeCourseWeb.com



We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...



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File list
  • Udemy - Hands-On Introduction To Artificial Intelligence(Ai)
  • ~Get Your Files Here !/1 - Introduction/1 - What is Artificial Intelligence AI.mp4 10.2 MB
  • ~Get Your Files Here !/1 - Introduction/10 - Neural Networks Perceptron.mp4 27.7 MB
  • ~Get Your Files Here !/1 - Introduction/11 - What are Deep Neural Networks.mp4 20.1 MB
  • ~Get Your Files Here !/1 - Introduction/12 - Feed Forward Neural Networks FFNN Structure and Forward pass.mp4 24.4 MB
  • ~Get Your Files Here !/1 - Introduction/13 - Input Feed Forward Neural Networks FFNN.mp4 8 MB
  • ~Get Your Files Here !/1 - Introduction/14 - Learning Phase Feed Forward Neural Networks FFNN.mp4 64.6 MB
  • ~Get Your Files Here !/1 - Introduction/15 - Back propagation and learning step Feed Forward Neural Networks FFNN.mp4 29.6 MB
  • ~Get Your Files Here !/1 - Introduction/16 - Applications and Limitations of Feed Forward Neural Networks FFNN.mp4 4.9 MB
  • ~Get Your Files Here !/1 - Introduction/17 - CNN Introduction.mp4 25.7 MB
  • ~Get Your Files Here !/1 - Introduction/18 - CNN Convolution and Relu Layer.mp4 29.1 MB
  • ~Get Your Files Here !/1 - Introduction/19 - CNN Max Pooling Layer.mp4 15.8 MB
  • ~Get Your Files Here !/1 - Introduction/2 - Mapping human functions to AI technologies.mp4 16.3 MB
  • ~Get Your Files Here !/1 - Introduction/20 - CNN Example end to end.mp4 21.6 MB
  • ~Get Your Files Here !/1 - Introduction/21 - Recurrent Neural Network RNN.mp4 32.1 MB
  • ~Get Your Files Here !/1 - Introduction/22 - RNN Architecture.mp4 12.3 MB
  • ~Get Your Files Here !/1 - Introduction/23 - Generative Adversarial Networks GAN.mp4 22.7 MB
  • ~Get Your Files Here !/1 - Introduction/24 - Reinforcement Learning.mp4 29.6 MB
  • ~Get Your Files Here !/1 - Introduction/25 - Transfer Learning.mp4 31.2 MB
  • ~Get Your Files Here !/1 - Introduction/26 - Market Potential of AI.mp4 23.9 MB
  • ~Get Your Files Here !/1 - Introduction/27 - Who will loose to AI.mp4 59.8 MB
  • ~Get Your Files Here !/1 - Introduction/28 - Need for retraining and reskilling.mp4 18.3 MB
  • ~Get Your Files Here !/1 - Introduction/29 - How to take advantage and benefit from AI.mp4 31.9 MB
  • ~Get Your Files Here !/1 - Introduction/3 - AI Branches of Machine Learning Algorithms.mp4 23.7 MB
  • ~Get Your Files Here !/1 - Introduction/4 - AI Supervised Machine Learning Algorithms and Applications.mp4 25.4 MB
  • ~Get Your Files Here !/1 - Introduction/5 - AI Unsupervised Machine Learning Algorithms and Applications.mp4 19.9 MB
  • ~Get Your Files Here !/1 - Introduction/6 - AI Natural Language Processing and Applications.mp4 37.3 MB
  • ~Get Your Files Here !/1 - Introduction/7 - AI Computer Vision and Applications.mp4 74.6 MB
  • ~Get Your Files Here !/1 - Introduction/8 - AI IOT and Applications.mp4 62.3 MB
  • ~Get Your Files Here !/1 - Introduction/9 - What are Neural Networks.mp4 12.5 MB
  • ~Get Your Files Here !/2 - IBM Watson Supervised and Unsupervised Machine Learning Models/30 - Building Supervised and Unsupervised Machine learning Models using IBM Watson.mp4 14.2 MB
  • ~Get Your Files Here !/2 - IBM Watson Supervised and Unsupervised Machine Learning Models/31 - Approach to building machine learning Models.mp4 40.7 MB
  • ~Get Your Files Here !/2 - IBM Watson Supervised and Unsupervised Machine Learning Models/32 - Account Setup and Configuration.mp4 32 MB
  • ~Get Your Files Here !/2 - IBM Watson Supervised and Unsupervised Machine Learning Models/33 - Supervised Building a Binary classificationML model and Uploading Data.mp4 12.2 MB
  • ~Get Your Files Here !/2 - IBM Watson Supervised and Unsupervised Machine Learning Models/34 - Supervised Training and testing your model using logistic regression.mp4 41.5 MB
  • ~Get Your Files Here !/2 - IBM Watson Supervised and Unsupervised Machine Learning Models/35 - Supervised Building a Multi class classificationML model end to end.mp4 51 MB
  • ~Get Your Files Here !/2 - IBM Watson Supervised and Unsupervised Machine Learning Models/36 - Unsupervised Building a RegressiveML Model end to end.mp4 36 MB
  • ~Get Your Files Here !/2 - IBM Watson Supervised and Unsupervised Machine Learning Models/37 - Performance Evaluation Parameters for ML Algorithms.mp4 20.2 MB
  • ~Get Your Files Here !/3 - Natural Language Processing NLP with IBM Watson/38 - Introduction to the Section.mp4 15.2 MB
  • ~Get Your Files Here !/3 - Natural Language Processing NLP with IBM Watson/39 - IBM Watson Text to Speech.mp4 40.6 MB
  • ~Get Your Files Here !/3 - Natural Language Processing NLP with IBM Watson/40 - IBM Watson Speech to Text.mp4 33.5 MB
  • ~Get Your Files Here !/3 - Natural Language Processing NLP with IBM Watson/41 - IBM Watson Semantic extraction.mp4 68 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/42 - Introduction to the Section and the experiment sheet.mp4 26 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/43 - Building a Perceptron.mp4 21.9 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/44 - Building a Feed Forward Neural Network with one Hidden layer Supervised.mp4 28.7 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/45 - Building a Deep Feed Forward Neural Network Supervised.mp4 46.4 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/46 - High Level Introduction to Tensor Flow Data and Setup Unsupervised.mp4 25.6 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/47 - Building a Regressive Feed Forward Neural NetworkFFNN Unsupervised.mp4 74.8 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/48 - Building a SHALLOW Regressive Feed Forward Neural Network Unsupervised.mp4 26.7 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/49 - Building a DEEP Regressive FFNN Unsupervised.mp4 32 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/50 - Building a Regressive FFNN with different AdamOptimizer.mp4 29.8 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/51 - Building a Regressive FFNN with different learning Rates and Epochs.mp4 71 MB
  • ~Get Your Files Here !/4 - Feed Forward Neural Networks FFNN with Tensor Flow Simulator and Google Colab/52 - Performance Analysis of Feed Forward Neural Networks.mp4 41.5 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/53 - Section Introduction and data.mp4 35.3 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/54 - CNN for MNIST Architecture Walkthrough.mp4 7.2 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/55 - IBM Watson Account Setup Basics.mp4 32 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/56 - CNN Setup and First Run with MNIST example Part 1.mp4 88.2 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/57 - CNN Setup and First Run with MNIST example Part 2.mp4 65.3 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/58 - CNN for MNIST with SGD.mp4 35.9 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/59 - Optimizing CNN for MNIST.mp4 107 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/60 - CNN for CIFAR 10.mp4 85.1 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/61 - Optimization options for CNN on CIFAR 10.mp4 72.3 MB
  • ~Get Your Files Here !/5 - Convolutional Neural Networks CNN with IBM Watson/62 - CNN Unconverging Experiments.mp4 37.1 MB
  • ~Get Your Files Here !/6 - Recurrent Neural Network RNN with Mathworks/63 - Introduction the section.mp4 11.3 MB
  • ~Get Your Files Here !/6 - Recurrent Neural Network RNN with Mathworks/64 - Japanese Vowels classification with LSTM Walk through of Mathworks example.mp4 122.9 MB
  • ~Get Your Files Here !/6 - Recurrent Neural Network RNN with Mathworks/65 - Classification of human activities with LSTM Walk through of Mathworks example.mp4 85.5 MB
  • ~Get Your Files Here !/Bonus Resources.txt 386 B

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