hours of learning
- 5 Real-life case
Neural Networks with TensorFlow
GPU Based EnvironmentThe program offers GPU based environment which enable learners to handle a GPU environment that are used in a real-world situation.
Live WebinarsLive webinars by experts for concept explanation and implementation through lab practice and assignments.
Live Meet-UpsWebinars, meet-ups or doubt-clearing sessions hosted by subject matter experts and professionals help the learners clear their doubts and queries.
Hands-on LearningSimple linear regression using TensorFlow, Solving quadratic equations using TensorFlow & Matrix multiplication with Tensorflow.
Case Studies & Demo CodesPractice on real case studies, ensures complete understanding and retention of the knowledge on each of the concepts.
Artificial Intelligence has allowed companies to realize cost-effective and time-effective ways of carrying out diverse business processes. AI applications like speech recognition, image recognition and pattern recognition are helping businesses make clever decisions. Evidently, with more businesses adopting AI and DL, the need for experts in the field is increasing.
Manipal ProLearn’s course on AI and DL takes you through the concepts of TensorFlow and Neural Networks. TensorFlow is a software library for performing complex numerical computations and helps in creating applications of Deep Learning. Neural Networks is the brain of Deep Learning. If you are pursuing a career in AI and DL, this combination of TensorFlow and Neural Networks is important to learn about. Also, through this course, you will gain experience in Python programming and using Keras, which is a neural-network library. –
By the end of the course, you would have learned about the importance of AI and DL. Also, you will gain practical knowledge with the tools – TensorFlow, Scikit and Keras. Through the study material and assignments, you are sure to become a pro at the subject. You will be able to
- Become Neural Networks expert by gaining a deep understanding of how Neural Networks works.
- Perform Simple Linear Regression and Matrix Multiplication with TensorFlow.
- Apply Tensorflow, Scikit Learn library, Keras and other machine learning and deep learning tools.
- Use Jupyter Notebook as the development environment for Python.
- Solve Quadratic Equations using TensorFlow.
- Get a very good understanding of how to navigate the complicated world of Tensorflow.
Experienced IT/ITES professionals who want to upgrade their skills in AI
IT freshers who want to start a career as a data scientist
Non-IT freshers with knowledge of programming, aspiring for a career in AI or Data Science
Introduction to Tensorflow.
Programming structure in Tensorflow
Variables, Constants and Placeholders, Sessions, Computational Graphs, Tensorboard
What is new in Tensorflow 2.0?
What is a Perceptron?
Implementing a perceptron
Recap of Matrix Multiplication
Deep Neural Networks
Training Neural networks with Tensorflow
Types of NN- CNN, RNN, Feedforward, GAN.
Common Tensorflow API - KERAS,
Introduction to Reinforcement Learning