Comprehensive Guide to Artificial Intelligence (AI)

Comprehensive Guide to Artificial Intelligence (AI)

  • By
  • Junaid Ahmed

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  • Clearly define AI and Deep Learning
  • Build Convolutional Neural Network on IBM Watson for MNIST and CIFAR 10 Datasets (No coding)
  • Build Supervised and Unsupervised Machine learning Models using IBM Watson (No coding)
  • Test Natural Language Processing (NLP) models using IBM Watson
  • Build VGG like nets, Stateful RNN nets, reuse ResNet50 using Keras
  • Test Reinforcement Learning with Keras and OpenAI Gym
  • Test Recurrent Neural Network (RNN) on Mathworks
  • Learn to code with Python the easy way
  • Test Feed Forward Neural Networks(Classification and Regression) on Tensor Flow simulator and Google Colab
  • Solve popular data sets like MNIST, CIFAR 10, with CNN using Keras
  • Learn a few useful and important application of popular libraries like Numpy, Pandas, Matplotlib
  • Migrate Deep Neural Network models from IBM Watson to run on local your Jupyter notebook
  • Apply Transfer Learning techniques such as Reusing, Retraining with Keras
  • Be able to identify the positive and the negative impact that AI will create