NVIDIA COPY

Question 1

Computer Vision, Natural Language Processing, Speech and Audio Processing, Robot learning more

Answer 1

Machine Deep Learning Frameworks

Question 2

A sub class of machine learning. It uses neural networks to train a model. Using very large data sets. In the range of Terabytes or more of data.

Answer 2

Deep Learning Approach

Question 3

Nueral Networks are Algorithms that mimic the human brain in understanding complex patterns

Answer 3

Deep Neural Network Model

Question 4

A set of data with labels that help the neural network learn. Labels can be the object in the images: cars, trucks, cranes. The error that the classifier makes on the training data are used to incrementally improve the network structure

Answer 4

Labeled Training Data

Question 5

Once the neural network based model is trained it can make predictions on new images. Once trained the network and classifier are deployed against previously unseen data, which is not labeled. If the training was done correctly, the network will be able to apply its feature representation to correctly classify similar classes in different situations.

Answer 5

Object Class Predictions

Question 6

A modern Open Source Deek learning framework used to train and deploy deep neural networks. It is scalable allowing for fast model training, and supports a flexible programming modem and multiple languages. This type of library is portable and can scale to multiple GPU’s and multiple machines.

Answer 6

Machine Deep Learning Frameworks - MXNet

Question 7

A free software machine learning library for Py Program language. It features various classification, regression and clustering algorithms and is designed to interoperate with the Python numberial and scientific libraries.

Answer 7

Machine Deep Learning Frameworks - SciKit

Question 8

Popular Open sores software library for dataflow programming across a rang of tasks. It is a symbolic math library and is commonly used for deep learning applications.

Answer 8

Machine Deep Learning Frameworks - Tensor Flow

Question 9

Host OS and NVIDIA Driver, NGC Container, DL Frameworks

Answer 9

Nvidia Deep Learning Software Stack

Question 10

Enables the deep learning framework to use the GPU functions

Answer 10

Host OS and Nvidia Drive

Question 11

Publicly available containers optimized to run the NVIDIA GPU’s

Answer 11

NGC Container

Question 12

Popular deep learning frameworks available inside the containers

Answer 12

DL Frameworks

Question 13

Data Prep, Model Train, Visulization

Answer 13

Machine Learning Software Stack

Question 14

Columnar in memory data strcuture which Delivers efficient and fast data interchange with flexibility to support complex data models

Answer 14

Apache arrow (Machine Learning Software Stack)

Question 15

A suite of open source software libraries and API’s. Offers the ability to execute end to end data science and analytics pipelines entirely on GPU’s

Answer 15

Rapids (Machine Learning Software Stack)

Question 16

A framework and collection of graph analytics libraries that seamlessly integrate into the RAPIDS data science platform.

Answer 16

CUGRAPH (Machine Learning Software Stack)

Question 17

A Dataframe manipulation library based on Apache Arrow that accelerates loading, filtering and manipulation of data for model training data preparation.

Answer 17

CUDF (Machine Learning Software Stack)

Question 18

A collection of GPU accelerated machine learning libraries that will provide GPU versions of all machine learning algorithms available, including SciKit-learn Knn, Kmeans, Random Forest and Regressions.

Answer 18

CUML (Machine learning software stack)

Question 19

Give users the ability to run jobs in the map reduce style of programming. Which allows pipelines to stage data in main memory if everything doesn’t fit in GPU memory.

Answer 19

DASK (Machine Learning Software Stack)

Question 20

Developers use this language which is a simple programming language, to develop models using the above libraries.

Answer 20

Python