What you’ll learn:
Artificial Neural Networks, Multilayered Perceptron
Convolutional Neural Networks, Recurrent Neural Networks,LSTM,GRUs
TensorFlow, Keras, Google Colab
Real World Projects and Case Studies
Requirements:
No Programming Experience, Basic knowledge of Data Science will be an advantage
Description:
This Course simplifies the advanced Deep Learning concepts like Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Long Short Term Memory (LSTM), Gated Recurrent Units(GRU), etc. TensorFlow, Keras, Google Colab, Real World Projects and Case Studies on topics like Regression and Classification have been described in great detail. Advanced Case studies like Self Driving Cars will be discussed in great detail. Currently the course has few case studies.The objective is to include at least 20 real world projects soon.
Case studies on topics like Object detection will also be included. TensorFlow and Keras basics and advanced concepts have been discussed in great detail. The ultimate goal of this course is to make the learner able to solve real world problems using deep learning. After completion of this course the Learner shall also be able to pass the Google TensorFlow Certification Examination which is one of the prestigious Certification. Learner will also get the certificate of completion from Udemy after completing the Course.
After taking this course the learner will be expert in following topics.
a) Theoretical Deep Learning Concepts.
b) Convolutional Neural Networks
c) Long-short term memory
d) Generative Adversarial Networks
e) Encoder- Decoder Models
f) Attention Models
g) Object detection
h) Image Segmentation
i) Transfer Learning
j) Open CV using Python
k) Building and deploying Deep Neural Networks
l) Professional Google Tensor Flow developer
m) Using Google Colab for writing Deep Learning code
n) Python programming for Deep Neural Networks
The Learners are advised to practice the Tensor Flow code as they watch the videos on Programming from this course.
First Few sections have been uploaded, The course is in updation phase and the remaining sections will be added soon.Who this course is for:Deep Learning beginnersStudents, Professionals, Learners who are curious about Deep Learning
Who this course is for:
Deep Learning beginners
Students, Professionals, Learners who are curious about Deep Learning
