Deeplearning.ai Deep Learning Specialization

(7 customer reviews)

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Doing this specialisation is probably more than the first step into Deep learning. It builds a fundamental understanding of the field. But going further, you have to practice a lot.

A person who has some basic understanding of maths, matrices and programming can benefit from this specialization and can have a good starting point to apply deep learning. On the other hand, the course can be a bit too basic for people who already have some experience in machine learning and deep learning.

Specification: Deeplearning.ai Deep Learning Specialization

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1. Neural Networks and Deep Learning – Introduction to deep learning, Neural Networks Basics, Shallow neural networks, Deep Neural Networks.
2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization – Practical aspects of Deep Learning, Optimization algorithms, Hyperparameter tuning, Batch Normalization and Programming Frameworks.
3. Structuring Machine Learning Projects – ML Strategy
4. Convolutional Neural Networks – Foundations of Convolutional Neural Networks, Deep convolutional models: case studies, Object detection, Special applications: Face recognition & Neural style transfer.
5. Sequence Models – Recurrent Neural Networks, Natural Language Processing & Word Embeddings, Sequence models & Attention mechanism.

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7 reviews for Deeplearning.ai Deep Learning Specialization

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  1. Vivek mankar

    Finally completed Specialization in deep Learning by deeplearning.ai. It was a great experience.

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  2. Noopur Gupta

    It has been incredible achieving the “Deep Learning Specialization” on Coursera by deeplearning.ai. 🎉

    Thanks to Andrew Ng for his great efforts in providing a deep dive into strong fundamentals and various state-of-the-art architectures and algorithms in such a simple format with fun assignments. 🙇‍♀️

    #deeplearning #neuralnetworks #ai #specialization #artificialintelligence #machinelearning #tensorflow #keras #python #coursera #coronalockdown

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  3. Sarthak garg

    Finished Andrew Ng’s Deep Learning Specialization by deeplearning.ai on Coursera. I must say, this Deep Learning Specialization is amazing and I genuinely loved it. It is dedicated to teaching you state of the art techniques and how to build them yourself. Prof. Andrew, in his inimitable style, teaches the concepts such that you understand them very well and thus is able to internalise. That is the key. If you’re a software developer who wants to get into building deep learning models or you’ve got a little programming experience and want to do the same, this course is for you. #artificialintelligence #coursera #machinelearning #deeplearning #AI #ANN #CNN #RNN #computervision #naturallanguageprocessing #datascience #python #tensorflow #keras #specialization

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  4. Abid Muin

    “Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning” is the first course of “TensorFlow in Practice” specialization from deeplearning.ai in Coursera.

    I’ve learned about how to use TensorFlow in various cases, how to tweak different parameters and implement different approaches to increase the accuracy of the model i.e. minimize the loss.

    I really enjoyed this course and looking forward to the next ones.

    #coursera #onlinecourse #ai #artificialintelligence #ml #machinelearning #deeplearning #specialization #python

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  5. Utkarsh Srivastava

    Finished Andrew Ng’s Deep Learning Specialization by deeplearning.ai on Coursera.

    I must say, this Deep Learning Specialization is amazing and I genuinely loved it. It is dedicated to teaching you state of the art techniques and how to build them yourself. Prof. Andrew, in his inimitable style, teaches the concepts such that you understand them very well and thus is able to internalize. That is the key.

    If you’re a software developer who wants to get into building deep learning models or you’ve got a little programming experience and want to do the same, this course is for you.

    #artificialintelligence #andrewng #coursera #machinelearning #deeplearning #AI #ANN #CNN #RNN #computervision #naturallanguageprocessing #datascience #python #tensorflow #keras #specialization

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  6. Fulong Tam

    Successfully completed deep learning specialization on Coursera offered by deeplearning.ai. It is a good fundamental course to start your deep learning path.

    Previously I involved myself in a deep learning research project related to computer vision field. However, without any prior knowledge on this field, I decided to take this specialisation to broaden my horizons. I learnt how to design the neural network from scratch, understood that the distribution of dataset will affect the model accuracy, fine-tuned the model to get better performance, applied different models into my research project such as VGG16, Generative Adversarial Privacy, ResNet.

    Currently I am looking for full time summer internship (may – aug) related to the area of Computer Vision/ Recommendation System/ NLP. I am highly interested in this expertise and I hope I can devote my knowledge to this area in the future. Please pm me if there is any opportunity.

    #deeplearning #artificialintelligence #computervision #coursera #ntu #eee #recommendationsystem #NLP #internship

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  7. Ihor Shylo

    Just completed 5-months Deep Learning Specialization provided by deeplearning.ai on Coursera. Thank you very much Andrew Ng for making difficult stuff easy, fun programming exercises and great experience! I definitely recommend this degree to anyone who is interested in #deeplearning #ai #machinelearning and #datascience.

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    Expert Score 9
    Course Content
    9
    Learning Experience
    9.5
    Course Price
    9
    Credibility
    9.5
    Flexibility
    10
    PROS:
    • Taught by Andrew Ng. Andrew’s ability to clarify complicated topics in a very understandable ways is amazing. He goes deeper into the mechanics, why things work the way they work and also some of the theories behind them.
    • He makes you feel motivated to learn.
    • There is a YouTube version of the course, and you don’t need to pay for it, but you would only have access to the videos.
    CONS:
    • If you are a strict hands-on learner, this specialization is probably not for you.
    • It lacks the practical implementation. No end-to-end coding projects.
    • Bit too basic for people who already have some experience in machine learning and deep learning.
    • Data preparation is not taught.
    Deeplearning.ai Deep Learning Specialization
    Deeplearning.ai Deep Learning Specialization
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