Study Full Life Cycle of a Deep Studying Challenge. Implement completely different Neural networks utilizing Tensorflow & Keras
What you’ll study
You’ll study the entire life cycle of a Knowledge Science Challenge with Machine Studying and Deep Studying.
Study completely different Neural Networks like ANN, CNN and RNN.
Study pandas, numpy, matplotlib, sklearn, tensorflow which can be a number of the most vital python libraries utilized in Knowledge Science, ML and DL.
You’ll construct sensible tasks like Gold Value Prediction, Picture Class Prediction and Inventory Value Prediction utilizing completely different Neural networks.
Description
Deep studying is a subfield of machine studying that’s centered on constructing neural networks with many layers, referred to as deep neural networks. These networks are sometimes composed of a number of layers of interconnected “neurons” or “items”, that are easy mathematical features that course of info. The layers in a deep neural community are organized in a hierarchical method, with decrease layers processing fundamental options and better layers combining these options to symbolize extra summary ideas.
Deep studying fashions are skilled utilizing giant quantities of knowledge and highly effective computational assets, corresponding to graphics processing items (GPUs). Coaching deep studying fashions could be computationally intensive, however the fashions can obtain state-of-the-art efficiency on a variety of duties, together with picture classification, pure language processing, speech recognition, and lots of others.
There are several types of deep studying fashions, corresponding to feedforward neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and lots of extra. Every sort of mannequin is suited to a unique sort of drawback, and the selection of mannequin will rely on the precise process and the kind of information that’s obtainable.
IN THIS COURSE YOU WILL LEARN :
- Full Life Cycle of Knowledge Science Challenge.
- Essential Knowledge Science Libraries like Pandas, Numpy, Matplotlib, Seaborn, sklearn and many others…
- How to decide on acceptable Machine Studying or Deep Studying Mannequin in your venture
- Machine Studying Fundamentals
- Regression and Classification in Machine Studying
- Synthetic Neural Networks (ANN)
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Tensorflow and Keras
- Completely different tasks like Gold Value Prediction, Inventory Value Prediction, Picture Classification and many others…
ALL THE BEST !!!
Content material
Introduction
Numpy
Pandas
Matplotlib and Seaborn for Knowledge Visualization
Machine Studying Fundamentals
Synthetic Neural Networks (ANN)
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
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