Comprehensive Guide to Artificial Intelligence(AI) for All
Learn ML, NLP, Deep, Transfer and Reinforcement learning with IBM Watson, Tensorflow Sim, Keras, OpenAI Gym and more
This course has 3 parts, first 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.
Best Seller Course: Hands-On Machine Learning: Learn TensorFlow, Python, & Java!
What Will I Learn?
- Clearly define what is 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
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