- Supervised Learning: Supervised learning learns from a set of labeled data. It is an algorithm that predicts the outcome of new data based on previously known labeled data.
- Unsupervised Learning: In unsupervised machine learning, training is based on unlabeled data. In this algorithm, you don’t know the outcome or the label of the input data.
- Semi-Supervised Learning: The AI will learn from a dataset that is partly labeled. This is the combination of the two types above.
- Reinforcement Learning: Reinforcement learning is the algorithm that helps a system determine its behavior to maximize its benefits. Currently, it is mainly applied to Game Theory, where algorithms need to determine the next move to achieve the highest score.
Data annotation for machine learning is the process of labeling or tagging data to make it understandable and usable for machine learning algorithms. This involves adding metadata, such as categories, tags, or attributes, to raw data, making it easier for algorithms to recognize patterns and learn from the data.
In fact, data annotation, or AI data processing, was once the most unwanted process of implementing AI in real life. Data annotation AI is a crucial step in creating supervised machine-learning models where the algorithm learns from labeled examples to make predictions or classifications.
1) Cloud Computing -advantages - On Demand , Low Capex
VMs
Hypervisor
VM -> Containers
Microservices
github repo
usage: git [-v | --version] [-h | --help] [-C <path>] [-c <name>=<value>]
[--exec-path[=<path>]] [--html-path] [--man-path] [--info-path]
[-p | --paginate | -P | --no-pager] [--no-replace-objects] [--bare]
[--git-dir=<path>] [--work-tree=<path>] [--namespace=<name>]
[--config-env=<name>=<envvar>] <command> [<args>]
These are common Git commands used in various situations:
start a working area (see also: git help tutorial)
clone Clone a repository into a new directory
init Create an empty Git repository or reinitialize an existing one
work on the current change (see also: git help everyday)
add Add file contents to the index
mv Move or rename a file, a directory, or a symlink
restore Restore working tree files
rm Remove files from the working tree and from the index
examine the history and state (see also: git help revisions)
bisect Use binary search to find the commit that introduced a bug
diff Show changes between commits, commit and working tree, etc
grep Print lines matching a pattern
log Show commit logs
show Show various types of objects
status Show the working tree status
grow, mark and tweak your common history
branch List, create, or delete branches
commit Record changes to the repository
merge Join two or more development histories together
rebase Reapply commits on top of another base tip
reset Reset current HEAD to the specified state
switch Switch branches
tag Create, list, delete or verify a tag object signed with GPG
collaborate (see also: git help workflows)
fetch Download objects and refs from another repository
pull Fetch from and integrate with another repository or a local branch
push Update remote refs along with associated objects
'git help -a' and 'git help -g' list available subcommands and some
concept guides. See 'git help <command>' or 'git help <concept>'
to read about a specific subcommand or concept.
See 'git help git' for an overview of the system.
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