募捐 9月15日2024 – 10月1日2024
关于筹款
书籍搜索
书
募捐:
26.3% 达到
登录
登录
访问更多功能
个人推荐
Telegram自动程序
下载历史
发送到电子邮件或 Kindle
管理书单
保存到收藏夹
个人的
书籍请求
探索
Z-Recommend
书单
最受欢迎
种类
贡献
捐款
上载
Litera Library
捐赠纸质书籍
添加纸质书籍
Search paper books
我的 LITERA Point
搜索关键词
Main
搜索关键词
search
1
Practical Deep Learning at Scale with MLflow: Bridge the gap between offline experimentation and online production
Yong Liu
mlflow
pipeline
tracking
inference
step
ray
figure
server
explainability
models
databricks
experiment
python
command
scale
github
hpo
parameters
version
explainer
deployment
shap
output
input
metrics
implementing
prediction
github.com
pipelines
function
notebook
runs
tuning
sagemaker
challenges
remote
logging
logged
pyfunc
pytorch
implement
docker
cycle
folder
experiments
deploying
aws
understanding
reference
method
年:
2022
语言:
english
文件:
PDF, 5.28 MB
您的标签:
0
/
5.0
english, 2022
2
Practical Deep Learning at Scale with MLflow: Bridge the gap between offline experimentation and online production
Packt Publishing
Yong Liu
mlflow
pipeline
inference
tracking
step
figure
ray
server
models
experiment
databricks
explainability
python
command
version
scale
deployment
output
github
parameters
explainer
shap
github.com
input
hpo
prediction
metrics
runs
function
notebook
logged
implement
pytorch
sagemaker
docker
experiments
folder
tuning
logging
remote
method
practical
repository
pyfunc
deploy
pipelines
aws
execution
cycle
challenges
年:
2022
语言:
english
文件:
EPUB, 7.69 MB
您的标签:
0
/
5.0
english, 2022
3
Practical Deep Learning at Scale with MLflow: Bridge the gap between offline experimentation and online production
Packt Publishing
Yong Liu
mlflow
pipeline
tracking
inference
step
figure
ray
server
models
databricks
experiment
explainability
python
command
version
deployment
output
explainer
github
parameters
input
shap
github.com
hpo
prediction
metrics
runs
scale
function
notebook
logged
implement
sagemaker
folder
docker
pytorch
tuning
experiments
remote
logging
method
repository
practical
pyfunc
deploy
pipelines
aws
execution
cycle
challenges
年:
2022
语言:
english
文件:
PDF, 10.25 MB
您的标签:
5.0
/
5.0
english, 2022
4
Practical Deep Learning at Scale with MLflow: Bridge the gap between offline experimentation and online production
Packt Publishing
Yong Liu & Dr. Matei Zaharia
mlflow
pipeline
tracking
inference
step
figure
ray
server
models
databricks
experiment
explainability
python
command
version
deployment
output
explainer
github
parameters
input
shap
github.com
hpo
prediction
metrics
runs
scale
function
notebook
logged
implement
sagemaker
folder
docker
pytorch
tuning
experiments
remote
logging
method
repository
practical
pyfunc
deploy
pipelines
aws
execution
cycle
challenges
年:
2022
语言:
english
文件:
PDF, 10.50 MB
您的标签:
5.0
/
4.0
english, 2022
1
按照
此链接
或在 Telegram 上找到“@BotFather”机器人
2
发送 /newbot 命令
3
为您的聊天机器人指定一个名称
4
为机器人选择一个用户名
5
从 BotFather 复制完整的最后一条消息并将其粘贴到此处
×
×