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Learning the Top 5 Machine Learning Tools from some famous books
- Review fundamental concepts such as bias and variance
- Extract features from categorical variables, text, and images
- Predict the values of continuous variables using linear regression and K Nearest Neighbors
- Classify documents and images using logistic regression and support vector machines
- Create ensembles of estimators using bagging and boosting techniques
- Discover hidden structures in data using K-Means clustering
- Evaluate the performance of machine learning systems in common tasks
- Get up and running with TensorFlow, rapidly and painlessly
- Learn how to use TensorFlow to build deep learning models from the ground up
- Train popular deep learning models for computer vision and NLP
- Use extensive abstraction libraries to make development easier and faster
- Learn how to scale TensorFlow, and use clusters to distribute model training
- Deploy TensorFlow in a production setting
- Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm
- Fine-tune a neural network to improve the quality of results
- Use deep learning for image and audio processing
- Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases
- Identify problems for which Recurrent Neural Network (RNN) solutions are suitable
- Explore the process required to implement Autoencoders
- Evolve a deep neural network using reinforcement learning
- Rapid Miner