BigSpy
Adspy
SocialPeta
PowerAdSpy
AdFox
Pipiads
Telmar
Insightrackr
Scikit-learn
Pandas
NumPy
OpenCV
Dataiku
Exploratory
WEKA
htm.java
Bigspy is having a huge database that almost covers every ad type, niche and also any country. It has more than 1,000,000,000 ads from more than 40 countries and regions and more than 40 ad types and is growing. You can easily social media ads And funnels in a matter of seconds. Bigspy also provides an intuitive layout for both the beginners and the pro ones. This tool allows you to search ads according to your keywords, country, Types, landing page and many more in a row that will help in finding the best Ads possible. and In addition to knowing about ads on Facebook. You can also learn about ads on AdMob, Pinterest, platform. Of course, if you are an advertiser of an e-commerce platform, then congratulations! This platform also has a function called Shopify spy, and you can use the same function. The best part is that here you can discover monetization strategies of competing Publishers, track viral trends and attract more new advertisers.
BigSpy Scikit-learnBigSpy's answer
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Python, SQL, Vue, Elasticsearch, Redis ...
BigSpy's answer
For the struggles, I think it has always been differentiation. In todayโs industry, it is not enough to have a good solid product. It is important to outwit and outdo the competition to rise in a competitive marketplace. Therefore, we have been working on data collection, accuracy, and modeling optimization to acquire users and outcompete others. We hope to help our customers achieve at BigSpy; weโre constantly reminded of it.
BigSpy's answer
KILO.HEALTH, WELLECH, BRIO, LEEDIA, AVN ...
I've tried several ad spy tools, but BigSpy offers the best value for money. The database is massiveโespecially for Facebook and TikTok ads. It saves me hours of manual research and helps me spot trending products before the market gets saturated. If you run a dropshipping business or manage paid social, this is a non-negotiable part of the tech stack. Highly recommended for the "Ad Ideas" feature alone.
It has a huge database of ads on several social platforms, like Facebook, Instagram, Twitter, AdMob, Pinterest, and Yahoo, so we can check different ads for ads inspiration. Also, we can spy on competitors and track the performance of their ads to decide new marketing strategies.
Based on our record, Scikit-learn seems to be a lot more popular than BigSpy. While we know about 40 links to Scikit-learn, we've tracked only 1 mention of BigSpy. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Https://bigspy.com/ and https://poweradspy.com/ both do this (but they're kind of sketchy). Source: about 4 years ago
Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / about 2 months ago
Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / about 2 months ago
Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 2 months ago
Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 3 months ago
In practice, youโll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 5 months ago
Adspy - Adspy is an innovative and advanced solution that enables advertisers to discover winning strategies and maintain their top position.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
SocialPeta - Essential Ad Intelligence Platform, which provides massive Ad data about Top Networks, Creatives, and Advertisers.
NumPy - NumPy is the fundamental package for scientific computing with Python
PowerAdSpy - PowerAdSpy enables you to maximize profits without allocating funds for testing ads.
OpenCV - OpenCV is the world's biggest computer vision library
