Deep Learning with TensorFlow

If you want to break into AI, Piford Technology will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing.

AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. This course also teaches you how Deep Learning actually works. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions.

Deep Learning with TensorFlow
  • What is Data Science?
  • What does Data Science involve?
  • Era of Data Science
  • Business Intelligence vs Data Science
  • Life cycle of Data Science
  • Tools of Data Science
  • Introduction to Python
    • Python Basics
    • Python Sckit, Sklearn and scipy
  • Data Analysis Pipeline
  • What is Data Extraction
  • Data Wrangling
  • What is Deep Learning Learning?
  • Deep Learning Process Flow
  • Data Pre-Processing
    • Introduction to Dimensionality
    • Why Dimensionality Reduction
    • PCA
    • Feature Scaling by different scaling methods
    • Data Scaling by different scaling methods
  • The components of a deep neural network and how they work together.

  • The basic types of deep neural networks (MLP, CNN, RNN, LSTM) and the type of data each is designed for
  • A working knowledge of vocabulary, concepts, and algorithms used in deep learning
  • How to build:

  • An end-to-end model for recognizing hand-written digit images, using a multi-class Logistic Regression and MLP (Multi-Layered Perceptron)
  • A CNN (Convolution Neural Network) model for improved digit recognition
  • An RNN (Recurrent Neural Network) model to forecast time-series data
  • An LSTM (Long Short Term Memory) model to process sequential text data
  • Project Work