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---
language:
- en
license: mit
size_categories:
- 10M<n<100M
task_categories:
- text-classification
- table-question-answering
- fill-mask
- sentence-similarity
pretty_name: Movies Data with Embeddings
tags:
- movies
- embeddings
- sentiment
- vectors
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: rated
dtype: string
- name: writers
sequence: string
- name: runtime
dtype: float64
- name: num_mflix_comments
dtype: int64
- name: title
dtype: string
- name: cast
sequence: string
- name: plot
dtype: string
- name: directors
sequence: string
- name: type
dtype: string
- name: fullplot
dtype: string
- name: languages
sequence: string
- name: awards
struct:
- name: nominations
dtype: int64
- name: text
dtype: string
- name: wins
dtype: int64
- name: imdb
struct:
- name: id
dtype: int64
- name: rating
dtype: float64
- name: votes
dtype: int64
- name: plot_embedding
sequence: float64
- name: metacritic
dtype: float64
- name: countries
sequence: string
- name: genres
sequence: string
- name: poster
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 13739333
num_examples: 1017
- name: test
num_bytes: 5863663
num_examples: 434
download_size: 19321684
dataset_size: 19602996
---
This dataset was created from the HuggingFace dataset **AIatMongoDB/embedded_movies**
**Why was it needed?**
1. The original dataset is close to 25 GB, for learning and experiments it is an overkill
2. Data in the dataset needs to be cleaned up e.g., some features are Null that requires extra care
3. Some of the embeddings are missing
**How to use?**
* Use for sentiment analysis
* Text similarity (plot)
* Embeddings : ready to use with vector DB & search libraries
---
dataset_info:
features:
- name: rated
dtype: string
- name: writers
sequence: string
- name: runtime
dtype: float64
- name: num_mflix_comments
dtype: int64
- name: title
dtype: string
- name: cast
sequence: string
- name: plot
dtype: string
- name: directors
sequence: string
- name: type
dtype: string
- name: fullplot
dtype: string
- name: languages
sequence: string
- name: awards
struct:
- name: nominations
dtype: int64
- name: text
dtype: string
- name: wins
dtype: int64
- name: imdb
struct:
- name: id
dtype: int64
- name: rating
dtype: float64
- name: votes
dtype: int64
- name: plot_embedding
sequence: float64
- name: metacritic
dtype: float64
- name: countries
sequence: string
- name: genres
sequence: string
- name: poster
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 13791171
num_examples: 1021
- name: test
num_bytes: 5811892
num_examples: 430
download_size: 19323013
dataset_size: 19603063
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
license: mit
task_categories:
- text-classification
- question-answering
- zero-shot-classification
- sentence-similarity
- fill-mask
- text-to-speech
language:
- en
tags:
- movies
- embeddings
- sentiment analysis
pretty_name: Movies data with plot-embeddings
size_categories:
- 10M<n<100M
--- |