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Database Migration for .Net Core Projects
Actualités, Méthodes et organisation des process ITYou can find all my .Net core posts here.
I am adding a new post after a long break because I recently joined a new company called AttachingIt. It is an awesome security-related company, and now, I am going to work on this awesome product.
Source de l’article sur DZONE
The Tipping Point of Innovation
Développement applicatif, Innovation, Méthodes et organisation des process ITIs a no-code platform a means to an end? Simply to build custom applications easily?
The answer is both yes, and no.
Source de l’article sur DZone (Agile)
Making Machine Learning Accessible for Enterprises: Part 2
Actualités, Développement IoT, InnovationIn Part 1 of this series, we discussed the need for automation of data science and the need for speed and scale in data transformation and building models. In this part, we will discuss other critical areas of ML-based solutions like:
Model Explainability
Simpler Machine Learning models like linear and logistic regression have high interpretability, but may have limited accuracy. On the other hand, Deep Learning models have time and again produced high accuracy results, but are considered black boxes because of the machine’s inability to explain their decisions and actions to human users. With regulations like GDPR, model explainability is quickly becoming one of the biggest challenges for data scientists, legal teams, and enterprises. Explainable AI, commonly referred to as XAI, is becoming one of the most sought-after research areas in Machine Learning. Predictive accuracy and explainability are frequently subject to a trade-off; higher levels of accuracy may be achieved but at the cost of decreased levels of explainability. Unlike Kaggle, competitions where complex ensemble models are created to win competitions, for enterprises, model interpretability is very important. Loan Default Prediction model cannot be used to reject loan to a customer until the model is able to explain why a loan is being rejected. Also, it is often required at the model level as well as individual test instance level. At Model level, there is need to explain key features which are important and how variation in these features affect the model decision. Variable Importance and Partial Dependence plots are popularly used for this. For an individual test instance level, there are packages like “lime,” which help in explaining how black box models make a decision.
Source de l’article sur DZONE (AI)
The Cold Start Problem
Actualités, Méthodes et organisation des process ITHow do you operate a data-driven application before you have any data? This is known as the cold start problem.
We faced this problem all the time when I designed clinical trials at MD Anderson Cancer Center. We used Bayesian methods to design adaptive clinical trial designs, such as clinical trials for determining chemotherapy dose levels. Each patient’s treatment assignment would be informed by data from all patients treated previously.
Source de l’article sur DZONE
Pruning Issues and the Idle Bin
Développement applicatif, Méthodes et organisation des process ITPart of the job of a Product Owner is to pay attention to the list of issues in the issue tracker. Not just to get a feeling for the cadence of the project, but to have an impact on its direction.
Paying attention to the issues doesn’t mean just tracking down what bugs are still opened, mind you. Consider the case of a Product Owner with the release due date looming over the horizon: he or she needs to start looking at the list of remaining issues and take active steps to make sure that they are going to get done more or less on time.
Source de l’article sur DZone (Agile)
Deep Learning Using Keras: Lessons Learned
Actualités, Développement IoT, InnovationIf you are planning to experiment with deep learning models, Keras might be a good place to start. It’s a high-level API written in Python with backend support for Tensorflow, CNTK, and Theano.
For those of you who are new to Keras, you can read more at keras.io or a simple google search will take you to the basics and more on Keras.
Source de l’article sur DZONE (AI)
NoClassDefFoundError When Using Lambda Instead of Anonymous Class [Snippets]
Actualités, Méthodes et organisation des process ITIt’s recommended to use Lambda instead of the anonymous class, but there are some pitfalls, such as the potential
NoClassDefFoundError.
In this post, I will explore this error and how to avoid it. I have two classes, RequiredObject and OptionalObject. The latter one is optional at runtime, and optional dependency is common especially for this framework.
Source de l’article sur DZONE
Cangibrina – Admin Dashboard Finder Tool
Actualités, Sécurité de l'information et du SI, Sécurité de l’information, Sécurité du système d’informationCangibrina is a Python-based multi platform admin dashboard finder tool which aims to obtain the location of website dashboards by using brute-force, wordlists, Google, Nmap and robots.txt.
It is multi-threaded, supports modifying your user agent, using a TOR proxy, custom dorks, Nmap integration and can use both DuckDuckGo and Google.
Cangibrina Admin Dashboard Finder Requirements
Cangibrina Usage to Find Admin Dashboards
usage: cangibrina.py [-h] -u U [-w W] [-t T] [-v] [–ext EXT] [–user-agent]
[–tor] [–search] [–dork DORK] [–nmap [NMAP]]
Fast and powerful admin finder
optional arguments:
-h, –help show this help message and exit
-u U target site
-w W set wordlist (default: wl_medium)
-t T set threads number (default: 5)
-v enable verbose
–ext EXT filter path by target extension
–user-agent modify user-agent
–sub-domain search for sub domains instead of directories
–tor set TOR proxy
–search use google and duckduckgo to search
–dork DORK set custom dork
–nmap [NMAP] use nmap to scan ports and services
There are other specific tools in this area like WPScan for WordPress and DruPwn for Drupal – and in those cases the dashboard URLs are already known.
Read the rest of Cangibrina – Admin Dashboard Finder Tool now! Only available at Darknet.
Source de l’article sur Darknet
Planning: Risk Management to Manage Uncertainty
Développement applicatif, Méthodes et organisation des process ITMany organizations plan to create certainty, guarantees of some variety. What if we thought about Agile planning as a way to manage uncertainty?
When I look at long roadmaps with all the "must-do" feature sets and the pressure managers put on teams to commit to delivery, I wonder about this question:
Source de l’article sur DZone (Agile)
Python Lists of Tuples
Actualités, Méthodes et organisation des process ITIn this post we will talk about creating Python Lists of Tuples and how they can be used.
Python Lists
Lists in Python are simply an array. Here is a basic list of my favorite WoW Classes:
Source de l’article sur DZONE