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- Introduction to TensorFlow
- Computational Graph
- Stochastic Gradient Descent
- Visual TensorBoard
- Keras with TensorFlow
- Role of Activation functions in ANN network
- Activation Functions:
- Sigmoid (Binary)
- Softmax (Multiclass)
- ReLU (Linear)
- Introduction to ANN
- Concept of Perceptron
- Perceptron Training Rule
- Gradient Descent Rule
- Gradient Descent
- Stochastic Gradient Descent
- Backpropagation
- Some problems in ANN
- Overfitting and Capacity
- Cross Validation
- Feature Selection
- Regularization
- Hyperparameters
- Introduction to CNNs
- Principles behind CNNs
- Kernel and Multiple Filters
- CNN Image Classification demo
- Introduction to RNNs
- Unfolded RNNs
- Seq2Seq RNNs
- LSTM
- RNN applications
- Image Processing
- Natural Language Processing
- Speech Recognition
- Video Analytics
- Image Classification with CNN - Keras
- Natural Language Processing with NKTL live project
Deep Learning with Python courses will get you ready for an AI career. Deep Learning is also one of the highly coveted skills in the tech industry. This course covers popular Deep Learning algorithms: Convolutional Networks, BatchNorm, RNNs, etc., with the case studies from autonomous driving, healthcare, Natural language processing, etc., With this course, you will not only master the concept behind deep learning but also see the application of the real world.
DataMites™ provide flexible learning options from traditional classroom training, lastest virtual live classroom to distance course. Based on your location preference, you may have one or more learning options
This course is perfectly aligned to the current industry requirements and gives exposure to all latest techniques and tools. The course curriculum is designed by specialists in this field and monitored improved by industry practitioners on continual basis.
All certificates can be validated with your unique certification number at IABAC.org portal. You also get candidate login at exam.iabac.org , where can find your test results and other relevant validation details.
The results of the Exam are immediate, if you take online test at exam.iabac.org portal. The certificate issuance, as per IABAC™ terms, takes about 7-10 bussiness days for e-certificate.
No, the exam fees are already included in the course fee and you will not be charged extra.
Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constrains, your relation manager at DataMites™ shall assist you with part payment agreements
DataMites™ has a dedicated Placement Assistance Team(PAT), who work with candidates on individual basis in assisting for right Data Science job.
You get 100% refund training fee if you the training is not to your satisfaction but the exam fee will not be refunded as we pay to accreditation bodies. If the refund is due to your availability concerns, you may need to talk to the relationship manager and will be sorted out on case to case basis
DataMites™ provides loads of study materials, cheat sheets, data sets, videos so that you can learn and practice extensively. Along with study materials, you will get materials on job interviews, new letters with latest information on Data Science as well as job updates.
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.