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Coursera Deep Learning Specialization
Completed all the courses on 17th March, 2018.
Schedule of the Coursera Deep Learning Specialization Courses, which I started taking from Jan 2018. This specialization has five courses which are listed below with their end dates, for the current session. Even though the order of the course is as listed in table, but it is not necessary to take in that order.
| Course Name | Specific Topics Covered | Length | End Date |
|---|---|---|---|
| Neural Nets & Deep Learning Quiz: 2, Prog. Assignments: 4 | * Intro. to Deep Learning * Neural Nets Basics * Numpy & Vectorization * Gradient Descent & Back propagation * Shallow 1-layer nets * Deep Neural Nets Intro. * Parameters & hyperparameters | 4 weeks | 19/Feb |
| Improving Deep Neural Nets Quiz: 3, Prog. Assigments: 4 | * Regularization * Initialization, bias & variance * Tensorflow * Understanding drop-outs * Gradient checking * Mini-batch gradient descent * RMSprop * Adam Optimization algo. * Hyperparams tuning - Pandas & Caviar * Fitting Batch Norm * Softmax regression | 3 weeks | 12/Mar |
| Structuring Machine Learning Projects Quiz on Case study: 2 | * Orthogonalization * Train/dev/test distribution & sizing * Avoidable bias * Bias/variance with mismatched data distr. * Transfer learning * Multitask Learning * End-to-end Deep Learning | 2 weeks | 19/Feb |
| Convolutional Neural Nets Quiz: 4, Prog. Assigments: 6 | * Computer vision * Edge detection * Strided convolutions * Simple CNN example * ResNets, Inception Nets * Transfer learning, Data Augmentation * State of Computer Vision * Keras tutorial * Residual nets * Object detection & YOLO algo * Face detection & Neural style transfer | 4 weeks | 05/Mar |
| Sequence Models Quiz: 3, Prog. Assigments: 7 | * RNNs & backprop thru' time * Gated Recurrent Unit & LSTM * Bi-directional & Deep RNNs * NLP & Word embeddings * Attention Model * Speech Recognition | 3 weeks | 21/Feb |
Courses Completion - Time-table
Note: Scheduling of other weeks for IDNN & CNN have to be done - Target 15/Feb. These schedule can follow the actual course weekly completion dead-lines.
| Date | Course | Activity | Est. Time | Actual Time | Milestone/Comments |
|---|---|---|---|---|---|
| 11/Feb | NNDL | Quiz 3 | 0.5 hrs | 0.75 hrs | Scored 1 mark less 'coz of not reviewing answers. |
| 11/Feb | NNDL | Quiz 4 | 0.5 hrs | 0.5 hrs | Scored full |
| 11/Feb | SM | Wk 1 - Videos & Notes | 1.0 hrs | ||
| 11/Feb | SM | Quiz 1, PA-1, PA-2, PA-3 | 2.0 hrs | ||
| 18/Feb | NNDL | PA-3, PA-4 | 2 hrs | Completed NNDL | |
| 13/Feb | SMLP | Wk 1 - Videos & Notes | 1.5 hr | hr | |
| 13/Feb | SMLP | Case study 1 | 1 hr | hr | |
| 14/Feb | CNN | Wk 1 - Videos & Notes | 1.5 hr | hr | |
| 14/Feb | CNN | Quiz, PA-1, PA-2 | 2.0 hr | hr | |
| 15/Feb | SMLP | Wk 2 - Videos & Notes | 3 hrs | ||
| 11/Mar | SMLP | Case study 2 | 1 hr | hr | Completed SMLP |
| 16/Feb | IDNN | Wk 1 - Videos & Notes | 5 hrs | hrs | |
| 17/Feb | IDNN | Quiz 1, PA-1, PA-2 | 3 hrs | hrs | |
| 17/Feb | SM | Wk 2 - Videos & Notes | 4 hrs | hrs | |
| 18/Feb | SM | Quiz 2, PA-4, PA-5 | 1.5 hrs | hrs | |
| 18/Feb | SM | Wk 3 - Videos & Notes | 4.5 hrs | hrs | |
| 05/Mar | SM | Quiz 3, PA-6, PA-7 | 2 hrs | hrs | Completed SM |
| 19/Feb | CNN | Wk 2 - Videos & Notes | 5 hrs | hrs | |
| 24/Feb | IDNN | Wk 2 - Videos & Notes | 4 hrs | hrs | |
| 17/Mar | CNN | Quiz 4, PA-5, PA-6 | 3 hrs | hrs | Completed CNN |
| 07/Mar | IDNN | Quiz 3, PA-4 | 1.5 hrs | hrs | Completed IDNN |
Other references for this courses include:
Updated