Convex Optimization in Python using CVXPY and PULP 2023 [Step by Step]

Convex optimization (cvxpy) and linear programming optimization (pulp) in python are demonstrated for solving linear and nonlinear programming objective function, subject to general constraints. EXCEL SOLVER IN PYTHON. Click "Show more" to learn more 👇:

𝐆𝐞𝐭 𝐢𝐧𝐬𝐭𝐚𝐧𝐭 𝐮𝐩𝐝𝐚𝐭𝐞𝐬 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐥𝐚𝐭𝐞𝐬𝐭 𝐯𝐢𝐝𝐞𝐨𝐬:

CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY has been used in hundreds of research projects and by Fortune 500 companies.

𝐌𝐚𝐤𝐞 𝐬𝐮𝐫𝐞 𝐭𝐨 𝐬𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐬𝐨 𝐲𝐨𝐮 𝐝𝐨𝐧'𝐭 𝐦𝐢𝐬𝐬 𝐨𝐮𝐭 𝐨𝐧 𝐦𝐲 𝐟𝐮𝐭𝐮𝐫𝐞 𝐯𝐢𝐝𝐞𝐨𝐬:

After subscribing, 𝐠𝐞𝐭 𝐟𝐫𝐞𝐞 𝐚𝐜𝐜𝐞𝐬𝐬 𝐭𝐨 𝐦𝐲 𝐆𝐨𝐨𝐠𝐥𝐞 𝐃𝐫𝐢𝐯𝐞: Follow steps on my YouTube Channel.

⌚𝐓𝐢𝐦𝐞𝐒𝐭𝐚𝐦𝐩𝐬:
Introduction (0:00)
Get FREE access to my Google Drive (0.50)
What is Convex Optimization (1:38)
Pulp (9:17)
cvxpy (16:30)

I used Anaconda jupyterlab for this code. It is an amazing platform for beginners.

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[rezatalaa]

hi, i was looking for dual variables in cvxpy python
if you are familiar with cvx in matlab it gets the constraints Lets say
cvx_begin
variable x1(n)
dual variable l1
minimize (c1'*x1 + 0.1*x1'*x1)
A1*x1 <= b1
l1 : D1*x1 <= t
cvx_end
f1 = cvx_optval;
can you help me with it in python i cant really understandthis part's documentation

[TheSouravrocks]

Can I use cvxpy for the linear problem too?