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Quick facts
particular | details | ||
---|---|---|---|
Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Frequency of Classes
Weekdays, Weekends
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Course and certificate fees
certificate availability
Yes
certificate providing authority
Mindmajix Technologies
The syllabus
Library used in Deep Learning
Artificial Neural Networks
- ANN Intuition
- The Neuron
- The Activation Function
- How do Neural Networks work?
- How do Neural Networks learn?
- Gradient Descent
- Stochastic Gradient Descent
- Back propagation
- Building an ANN
- Installing Keras
- Evaluating the ANN
- Improving the ANN
- Tuning the ANN
Image Preprocessing
- Matplotlib
- Pillow
- OpenCV
Convolutional Neural Networks
- CNN Intuition
- What You'll Need for CNN
- What are convolutional neural networks?
- Step 1(a) - Convolution Operation
- Step 1(b) - ReLU Layer
- Step 2 - Pooling
- Step 3 - Flattening
- Step 4 - Full Connection
- Softmax & Cross-Entropy
- Building a CNN
- Evaluating CNN
- Improving CNN
- Tuning the CNN
Recurrent Neural Networks
- RNN Intuition
- The idea behind Recurrent Neural Networks
- The Vanishing Gradient Problem
- LSTMs
- Practical intuition
- EXTRA: LSTM Variations
- Building a RNN
- Evaluating RNN
- Improving RNN
- Tuning RNN
Self Organizing Maps
- SOMs Intuition
- How do Self-Organizing Maps Work?
- Why revisit K-Means?
- K-Means Clustering (Refresher)
- How do Self-Organizing Maps Learn?
- Reading an Advanced SOM?
Natural Language Processing (NLP with Implementation)
- Tokenization
- Stemming
- Lemmatization
- POS TagName
- Entity Recognition