Deep Learning for Beginners in Python: Work On 12+ Projects

Udemy Deep Learning for Beginners in Python: Work On 12+ Projects

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What you'll learn
  • Complete Understanding of Deep Learning from the Scratch
  • Building the Artificial Neural Networks (ANNs) from the Scratch
  • Artificial Neural Networks (ANNs) for Binary Data Classification
  • Building Convolutional Neural Networks from the Scratch
  • Convolutional Neural Network for Image Classification
  • Convolutional Neural Network for Digit Recognition
  • Breast Cancer Detection with Convolutional Neural Networks
  • Convolutional Neural Networks for Predictive Analysis
  • Convolutional Neural Networks for Fraud Detection
  • Building the Recurrent Neural Networks (ANNs) from Scratch
  • LSTM and GRU
  • Review Classification with LSTM and GRU
  • LSTM and GRU for Image Classification
  • Prediction of Google Stock Price with RNN and LSTM
  • Transfer Learning
  • Natural Language Processing
  • Crash Course on Numpy (Data Analysis)
  • Crash Course on Pandas (Data Analysis)
  • Crash course on Matplotlib (Data Visualization)
Description
The Artificial Intelligence and Deep Learning are growing exponentially in today's world. There are multiple application of AI and Deep Learning like Self Driving Cars, Chat-bots, Image Recognition, Virtual Assistance, ALEXA, so on...
With this course you will understand the complexities of Deep Learning in easy way, as well as you will have A Complete Understanding of Googles TensorFlow 2.0 Framework
TensorFlow 2.0 Framework has amazing features that simplify the Model Development, Maintenance, Processes and Performance
In TensorFlow 2.0 you can start the coding with Zero Installation, whether you’re an expert or a beginner, in this course you will learn an end-to-end implementation of Deep Learning Algorithms

List of the Projects that you will work on,
Part 1: Artificial Neural Networks (ANNs)
Project 1: Multiclass image classification with ANN
Project 2: Binary Data Classification with ANN
Part 2: Convolutional Neural Networks (CNNs)
Project 3: Object Recognition in Images with CNN
Project 4: Binary Image Classification with CNN
Project 5: Digit Recognition with CNN
Project 6: Breast Cancer Detection with CNN
Project 7: Predicting the Bank Customer Satisfaction
Project 8: Credit Card Fraud Detection with CNN
Part 3: Recurrent Neural Networks (RNNs)
Project 9: IMDB Review Classification with RNN - LSTM
Project 10: Multiclass Image Classification with RNN - LSTM
Project 11: Google Stock Price Prediction with RNN and LSTM
Part 4: Transfer Learning
Part 5: Natural Language Processing

Basics of Natural Language Processing
Project 12: Movie Review Classifivation with NLTK
Part 6: Data Analysis and Data Visualization
Crash Course on Numpy (Data Analysis)
Crash Course on Pandas (Data Analysis)
Crash course on Matplotlib (Data Visualization)

With this course you will learn,
1) To built the Neural Networks from the scratch
2) You will have a complete understanding of Artificial Neural Networks, Convolutional Neural Networks and Recurrent Neural Networks
3) You will learn to built the neural networks with LSTM and GRU
4) Hands On Transfer Learning
5) Learn Natural Language Processing by doing a text classifiation project
6) Improve your skills in Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib

So what are you waiting for, Enroll Now and understand Deep Learning to advance your career and increase your knowledge !

Regards,
Vijay Gadhave
Who this course is for:
  • Anyone who wants to learn Deep Learning and AI
  • Students and Professionals who want to start a career in Data Science, Deep Learning and AI
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TUTProfessor
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