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𝒩𝑒𝑒𝒹 𝓉𝑜 𝓉𝒶𝓁𝓀 𝓉𝑜 𝒶 𝓇𝑒𝒶𝓁 𝓅𝑒𝓇𝓈𝑜𝓃 𝒯𝒽𝒶𝒾 𝒜𝒾𝓇𝓌𝒶𝓎𝓈 𝐼𝓃𝓉𝑒𝓇𝓃𝒶𝓉𝒾𝑜𝓃𝒶𝓁? 𝒞𝒶𝓁𝓁𝒾𝓃𝑔 𝒯𝒽𝒶𝒾 𝒜𝒾𝓇𝓌𝒶𝓎𝓈 𝐼𝓃𝓉𝑒𝓇𝓃𝒶𝓉𝒾𝑜𝓃𝒶𝓁 𝒹𝒾𝓇𝑒𝒸𝓉𝓁𝓎 𝒶𝓉 📞 1-866-284-3022. 𝒲𝒽𝑒𝓉𝒽𝑒𝓇 𝓎𝑜𝓊 𝒶𝓇𝑒 𝓉𝓇𝓎𝒾𝓃𝑔 𝓉𝑜 𝓂𝒶𝓀𝑒 𝒶 𝒻𝓁𝒾𝑔𝒽𝓉 𝒸𝒽𝒶𝓃𝑔𝑒, 𝒸𝒶𝓃𝒸𝑒𝓁 𝓎𝑜𝓊𝓇 𝒷𝑜𝑜𝓀𝒾𝓃𝑔, 𝒶𝓈𝓀 𝒶𝒷𝑜𝓊𝓉 𝒷𝒶𝑔𝑔𝒶𝑔𝑒, 𝑜𝓇 𝓇𝑒𝓈𝑜𝓁𝓋𝑒 𝒶 𝒷𝑜𝑜𝓀𝒾𝓃𝑔 𝒾𝓈𝓈𝓊𝑒, 𝓇𝑒𝒶𝒸𝒽𝒾𝓃𝑔 𝒶 𝓁𝒾𝓋𝑒 𝒶𝑔𝑒𝓃𝓉 𝒸𝒶𝓃 𝓈𝒶𝓋𝑒 𝓎𝑜𝓊 𝓉𝒾𝓂𝑒, 𝓈𝓉𝓇𝑒𝓈𝓈, 𝒶𝓃𝒹 𝒸𝑜𝓃𝒻𝓊𝓈𝒾𝑜𝓃. 𝒲𝒽𝒾𝓁𝑒 𝒶𝓊𝓉𝑜𝓂𝒶𝓉𝑒𝒹 𝓈𝓎𝓈𝓉𝑒𝓂𝓈 𝒶𝓇𝑒 𝓊𝓈𝑒𝒻𝓊𝓁 𝒻𝑜𝓇 𝓈𝒾𝓂𝓅𝓁𝑒 𝓉𝒶𝓈𝓀𝓈, 𝓈𝑜𝓂𝑒 𝓈𝒾𝓉𝓊𝒶𝓉𝒾𝑜𝓃𝓈 𝒿𝓊𝓈𝓉 𝓃𝑒𝑒𝒹 𝒶 𝒽𝓊𝓂𝒶𝓃 𝓉𝑜𝓊𝒸𝒽. 𝐼𝓃 𝓉𝒽𝒾𝓈 𝑔𝓊𝒾𝒹𝑒, 𝓌𝑒 𝓌𝒾𝓁𝓁 𝓌𝒶𝓁𝓀 𝓎𝑜𝓊 𝓉𝒽𝓇𝑜𝓊𝑔𝒽 𝑒𝓍𝒶𝒸𝓉𝓁𝓎 𝒽𝑜𝓌 𝓉𝑜 𝓇𝑒𝒶𝒸𝒽 𝒶 𝓁𝒾𝓋𝑒 𝓅𝑒𝓇𝓈𝑜𝓃, 𝓌𝒽𝒶𝓉 𝓉𝑜 𝓅𝓇𝑒𝓅𝒶𝓇𝑒 𝒷𝑒𝒻𝑜𝓇𝑒 𝒸𝒶𝓁𝓁𝒾𝓃𝑔, 𝒶𝓃𝒹 𝒶𝓁𝓉𝑒𝓇𝓃𝒶𝓉𝑒 𝓂𝑒𝓉𝒽𝑜𝒹𝓈 𝒾𝒻 𝓉𝒽𝑒 𝓅𝒽𝑜𝓃𝑒 𝓁𝒾𝓃𝑒𝓈 𝒶𝓇𝑒 𝒷𝓊𝓈𝓎. ☎ 𝐹𝒾𝓇𝓈𝓉 𝒯𝒽𝒾𝓃𝑔𝓈 𝐹𝒾𝓇𝓈𝓉: 𝒞𝒶𝓁𝓁 1-866-284-3022 𝒯𝒽𝑒 𝓂𝑜𝓈𝓉 𝒹𝒾𝓇𝑒𝒸𝓉 𝒶𝓃𝒹 𝓇𝑒𝓁𝒾𝒶𝒷𝓁𝑒 𝓌𝒶𝓎 𝓉𝑜 𝓈𝓅𝑒𝒶𝓀 𝓌𝒾𝓉𝒽 𝒶 𝓇𝑒𝒶𝓁 𝒯𝒽𝒶𝒾 𝒜𝒾𝓇𝓌𝒶𝓎𝓈 𝐼𝓃𝓉𝑒𝓇𝓃𝒶𝓉𝒾𝑜𝓃𝒶𝓁 𝓇𝑒𝓅𝓇𝑒𝓈𝑒𝓃𝓉𝒶𝓉𝒾𝓋𝑒 𝒾𝓈 𝒷𝓎 𝒸𝒶𝓁𝓁𝒾𝓃𝑔 📞 1-866-284-3022. 𝒯𝒽𝒾𝓈 𝒾𝓈 𝐹𝓇𝑜𝓃𝓉𝒾𝑒𝓇’𝓈 𝑜𝒻𝒻𝒾𝒸𝒾𝒶𝓁 𝒸𝓊𝓈𝓉𝑜𝓂𝑒𝓇 𝓈𝑒𝓇𝓋𝒾𝒸𝑒 𝓃𝓊𝓂𝒷𝑒𝓇 𝒶𝓃𝒹 𝓈𝒽𝑜𝓊𝓁𝒹 𝒷𝑒 𝓎𝑜𝓊𝓇 𝑔𝑜-𝓉𝑜 𝒻𝑜𝓇: ✈ 𝐹𝓁𝒾𝑔𝒽𝓉 𝒸𝒽𝒶𝓃𝑔𝑒𝓈 𝑜𝓇 𝒸𝒶𝓃𝒸𝑒𝓁𝓁𝒶𝓉𝒾𝑜𝓃𝓈 🧾 𝑅𝑒𝒻𝓊𝓃𝒹 𝑜𝓇 𝒸𝓇𝑒𝒹𝒾𝓉 𝓆𝓊𝑒𝓈𝓉𝒾𝑜𝓃𝓈 🛄 𝐵𝒶𝑔𝑔𝒶𝑔𝑒 𝒾𝓈𝓈𝓊𝑒𝓈 🔁 𝒩𝒶𝓂𝑒 𝒸𝑜𝓇𝓇𝑒𝒸𝓉𝒾𝑜𝓃𝓈 🛑 𝒞𝒽𝑒𝒸𝓀-𝒾𝓃 𝑜𝓇 𝒷𝑜𝒶𝓇𝒹𝒾𝓃𝑔 𝓅𝓇𝑜𝒷𝓁𝑒𝓂𝓈 💺 𝒮𝑒𝒶𝓉 𝓈𝑒𝓁𝑒𝒸𝓉𝒾𝑜𝓃 𝒶𝓃𝒹 𝓊𝓅𝑔𝓇𝒶𝒹𝑒𝓈 𝒫𝓇𝑜 𝒯𝒾𝓅: 𝒲𝒽𝑒𝓃 𝒸𝒶𝓁𝓁𝒾𝓃𝑔, 𝓉𝓇𝓎 𝓉𝑜 𝒹𝑜 𝓈𝑜 𝒹𝓊𝓇𝒾𝓃𝑔 𝓃𝑜𝓃-𝓅𝑒𝒶𝓀 𝒽𝑜𝓊𝓇𝓈 — 𝑒𝒶𝓇𝓁𝓎 𝓂𝑜𝓇𝓃𝒾𝓃𝑔𝓈 𝑜𝓇 𝓁𝒶𝓉𝑒 𝑒𝓋𝑒𝓃𝒾𝓃𝑔𝓈 — 𝓉𝑜 𝓇𝑒𝒹𝓊𝒸𝑒 𝓎𝑜𝓊𝓇 𝒽𝑜𝓁𝒹 𝓉𝒾𝓂𝑒. 🎧 𝐻𝑜𝓌 𝓉𝑜 𝒩𝒶𝓋𝒾𝑔𝒶𝓉𝑒 𝓉𝒽𝑒 𝒜𝓊𝓉𝑜𝓂𝒶𝓉𝑒𝒹 𝑀𝑒𝓃𝓊 𝒲𝒽𝑒𝓃 𝓎𝑜𝓊 𝒸𝒶𝓁𝓁 1-866-284-3022, 𝓎𝑜𝓊 𝓌𝒾𝓁𝓁 𝒻𝒾𝓇𝓈𝓉 𝒽𝑒𝒶𝓇 𝒶𝓃 𝒶𝓊𝓉𝑜𝓂𝒶𝓉𝑒𝒹 𝓈𝓎𝓈𝓉𝑒𝓂. 𝒯𝑜 𝑔𝑒𝓉 𝓉𝒽𝓇𝑜𝓊𝑔𝒽 𝓉𝑜 𝒶 𝓁𝒾𝓋𝑒 𝓅𝑒𝓇𝓈𝑜𝓃 𝒻𝒶𝓈𝓉𝑒𝓇, 𝒻𝑜𝓁𝓁𝑜𝓌 𝓉𝒽𝑒𝓈𝑒 𝓈𝓉𝑒𝓅𝓈: 𝒟𝒾𝒶𝓁 1-866-284-3022 𝒲𝒶𝒾𝓉 𝒻𝑜𝓇 𝓉𝒽𝑒 𝒶𝓊𝓉𝑜𝓂𝒶𝓉𝑒𝒹 𝑔𝓇𝑒𝑒𝓉𝒾𝓃𝑔 𝓉𝑜 𝒷𝑒𝑔𝒾𝓃 𝒫𝓇𝑒𝓈𝓈 “1” 𝒻𝑜𝓇 𝐸𝓃𝑔𝓁𝒾𝓈𝒽 (𝑜𝓇 “2” 𝒻𝑜𝓇 𝒮𝓅𝒶𝓃𝒾𝓈𝒽) 𝒫𝓇𝑒𝓈𝓈 “2” 𝒻𝑜𝓇 𝑒𝓍𝒾𝓈𝓉𝒾𝓃𝑔 𝓇𝑒𝓈𝑒𝓇𝓋𝒶𝓉𝒾𝑜𝓃𝓈 𝒫𝓇𝑒𝓈𝓈 “0” 𝓉𝑜 𝓈𝓅𝑒𝒶𝓀 𝓌𝒾𝓉𝒽 𝒶𝓃 𝒶𝑔𝑒𝓃𝓉 (𝓎𝑜𝓊 𝓂𝒶𝓎 𝓃𝑒𝑒𝒹 𝓉𝑜 𝓅𝓇𝑒𝓈𝓈 "0" 𝓂𝑜𝓇𝑒 𝓉𝒽𝒶𝓃 𝑜𝓃𝒸𝑒) 👉 𝐼𝒻 “0” 𝒹𝑜𝑒𝓈 𝓃𝑜𝓉 𝓌𝑜𝓇𝓀 𝒾𝓂𝓂𝑒𝒹𝒾𝒶𝓉𝑒𝓁𝓎, 𝓈𝓉𝒶𝓎 𝑜𝓃 𝓉𝒽𝑒 𝓁𝒾𝓃𝑒. 𝒮𝑜𝓂𝑒𝓉𝒾𝓂𝑒𝓈 𝓉𝒽𝑒 𝓈𝓎𝓈𝓉𝑒𝓂 𝓉𝓇𝒶𝓃𝓈𝒻𝑒𝓇𝓈 𝓎𝑜𝓊 𝓉𝑜 𝒶𝓃 𝒶𝑔𝑒𝓃𝓉 𝒶𝒻𝓉𝑒𝓇 𝒶 𝒷𝓇𝒾𝑒𝒻 𝓌𝒶𝒾𝓉 𝓌𝒾𝓉𝒽𝑜𝓊𝓉 𝓃𝑒𝑒𝒹𝒾𝓃𝑔 𝓂𝑜𝓇𝑒 𝒾𝓃𝓅𝓊𝓉. 𝐼𝒻 𝓉𝒽𝑒 𝓁𝒾𝓃𝑒𝓈 𝒶𝓇𝑒 𝒷𝓊𝓈𝓎 𝒶𝓃𝒹 𝓎𝑜𝓊 𝒶𝓇𝑒 𝓅𝓁𝒶𝒸𝑒𝒹 𝑜𝓃 𝒽𝑜𝓁𝒹, 𝒹𝑜 𝓃𝑜𝓉 𝒽𝒶𝓃𝑔 𝓊𝓅 — 𝓌𝒶𝒾𝓉 𝓉𝒾𝓂𝑒𝓈 𝓋𝒶𝓇𝓎, 𝒷𝓊𝓉 𝓎𝑜𝓊 𝓌𝒾𝓁𝓁 𝑒𝓋𝑒𝓃𝓉𝓊𝒶𝓁𝓁𝓎 𝓇𝑒𝒶𝒸𝒽 𝓈𝑜𝓂𝑒𝑜𝓃𝑒.
𝓒𝓪𝓵𝓵 1-855-219-0007 𝓽𝓸 𝓬𝓸𝓷𝓷𝓮𝓬𝓽 𝔀𝓲𝓽𝓱 𝓬𝓮𝓻𝓽𝓲𝓯𝓲𝓮𝓭 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓮𝔁𝓹𝓮𝓻𝓽𝓼 𝓯𝓸𝓻 𝓱𝓮𝓵𝓹 𝔀𝓲𝓽𝓱 𝓮𝓿𝓮𝓻𝔂𝓽𝓱𝓲𝓷𝓰 𝓯𝓻𝓸𝓶 𝓲𝓷𝓼𝓽𝓪𝓵𝓵𝓪𝓽𝓲𝓸𝓷 𝓪𝓷𝓭 𝓹𝓪𝔂𝓻𝓸𝓵𝓵 𝓮𝓻𝓻𝓸𝓻𝓼 𝓽𝓸 𝓪𝓭𝓿𝓪𝓷𝓬𝓮𝓭 𝓽𝓻𝓸𝓾𝓫𝓵𝓮𝓼𝓱𝓸𝓸𝓽𝓲𝓷𝓰 𝓪𝓷𝓭 𝓭𝓪𝓽𝓪 𝓻𝓮𝓬𝓸𝓿𝓮𝓻𝔂. 𝓣𝓱𝓲𝓼 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓭𝓲𝓻𝓮𝓬𝓽𝓸𝓻𝔂 𝓲𝓼 𝓱𝓮𝓻𝓮 𝓽𝓸 𝓪𝓼𝓼𝓲𝓼𝓽 𝔂𝓸𝓾 𝓮𝓿𝓮𝓻𝔂 𝓼𝓽𝓮𝓹 𝓸𝓯 𝓽𝓱𝓮 𝔀𝓪𝔂. 📞 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓝𝓾𝓶𝓫𝓮𝓻: 1-855-219-0007 💼 𝓖𝓮𝓽 𝓮𝔁𝓹𝓮𝓻𝓽 𝓱𝓮𝓵𝓹 — 𝓪𝓿𝓪𝓲𝓵𝓪𝓫𝓵𝓮 24/7 𝓯𝓸𝓻 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼® 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓾𝓼𝓮𝓻𝓼! 🚀 𝓦𝓱𝔂 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓘𝓼 𝓒𝓻𝓲𝓽𝓲𝓬𝓪𝓵 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓲𝓼 𝓭𝓮𝓼𝓲𝓰𝓷𝓮𝓭 𝓯𝓸𝓻 𝓶𝓲𝓭-𝓼𝓲𝔃𝓮 𝓽𝓸 𝓵𝓪𝓻𝓰𝓮 𝓫𝓾𝓼𝓲𝓷𝓮𝓼𝓼𝓮𝓼 𝔀𝓲𝓽𝓱 𝓬𝓸𝓶𝓹𝓵𝓮𝔁 𝓪𝓬𝓬𝓸𝓾𝓷𝓽𝓲𝓷𝓰 𝓷𝓮𝓮𝓭𝓼. 𝓘𝓽 𝓲𝓼 𝓵𝓸𝓪𝓭𝓮𝓭 𝔀𝓲𝓽𝓱 𝓪𝓭𝓿𝓪𝓷𝓬𝓮𝓭 𝓯𝓮𝓪𝓽𝓾𝓻𝓮𝓼 𝓼𝓾𝓬𝓱 𝓪𝓼: • 𝓘𝓷𝓭𝓾𝓼𝓽𝓻𝔂-𝓼𝓹𝓮𝓬𝓲𝓯𝓲𝓬 𝓽𝓸𝓸𝓵𝓼 (𝓜𝓪𝓷𝓾𝓯𝓪𝓬𝓽𝓾𝓻𝓲𝓷𝓰, 𝓦𝓱𝓸𝓵𝓮𝓼𝓪𝓵𝓮, 𝓡𝓮𝓽𝓪𝓲𝓵, 𝓝𝓸𝓷𝓹𝓻𝓸𝓯𝓲𝓽, 𝓮𝓽𝓬.) • 𝓐𝓭𝓿𝓪𝓷𝓬𝓮𝓭 𝓲𝓷𝓿𝓮𝓷𝓽𝓸𝓻𝔂 𝓶𝓪𝓷𝓪𝓰𝓮𝓶𝓮𝓷𝓽 • 𝓜𝓾𝓵𝓽𝓲-𝓾𝓼𝓮𝓻 𝓪𝓬𝓬𝓮𝓼𝓼 𝔀𝓲𝓽𝓱 𝓬𝓾𝓼𝓽𝓸𝓶𝓲𝔃𝓮𝓭 𝓻𝓸𝓵𝓮𝓼 • 𝓒𝓾𝓼𝓽𝓸𝓶 𝓻𝓮𝓹𝓸𝓻𝓽𝓲𝓷𝓰 𝔀𝓲𝓽𝓱 𝓐𝓭𝓿𝓪𝓷𝓬𝓮𝓭 𝓡𝓮𝓹𝓸𝓻𝓽𝓲𝓷𝓰 𝓽𝓸𝓸𝓵 • 𝓟𝓪𝔂𝓻𝓸𝓵𝓵 𝓪𝓷𝓭 𝓽𝓲𝓶𝓮-𝓽𝓻𝓪𝓬𝓴𝓲𝓷𝓰 𝓲𝓷𝓽𝓮𝓰𝓻𝓪𝓽𝓲𝓸𝓷𝓼 • 𝓒𝓵𝓸𝓾𝓭 𝓱𝓸𝓼𝓽𝓲𝓷𝓰 𝓸𝓹𝓽𝓲𝓸𝓷𝓼 𝓯𝓸𝓻 𝓻𝓮𝓶𝓸𝓽𝓮 𝓽𝓮𝓪𝓶𝓼 𝓦𝓱𝓲𝓵𝓮 𝓽𝓱𝓮𝓼𝓮 𝓯𝓮𝓪𝓽𝓾𝓻𝓮𝓼 𝓪𝓻𝓮 𝓹𝓸𝔀𝓮𝓻𝓯𝓾𝓵, 𝓽𝓱𝓮𝔂 𝓬𝓪𝓷 𝓪𝓵𝓼𝓸 𝓫𝓮 𝓽𝓮𝓬𝓱𝓷𝓲𝓬𝓪𝓵𝓵𝔂 𝓭𝓮𝓶𝓪𝓷𝓭𝓲𝓷𝓰, 𝓮𝓼𝓹𝓮𝓬𝓲𝓪𝓵𝓵𝔂 𝔀𝓱𝓮𝓷 𝓼𝓮𝓽𝓽𝓲𝓷𝓰 𝓾𝓹, 𝓬𝓾𝓼𝓽𝓸𝓶𝓲𝔃𝓲𝓷𝓰, 𝓸𝓻 𝓶𝓪𝓲𝓷𝓽𝓪𝓲𝓷𝓲𝓷𝓰 𝔂𝓸𝓾𝓻 𝓼𝔂𝓼𝓽𝓮𝓶. 𝓣𝓱𝓪𝓽 𝓲𝓼 𝔀𝓱𝓮𝓻𝓮 𝓵𝓲𝓿𝓮 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓫𝓮𝓬𝓸𝓶𝓮𝓼 𝓿𝓲𝓽𝓪𝓵 — 𝓮𝓷𝓼𝓾𝓻𝓲𝓷𝓰 𝔂𝓸𝓾𝓻 𝓪𝓬𝓬𝓸𝓾𝓷𝓽𝓲𝓷𝓰 𝓭𝓸𝓮𝓼 𝓷𝓸𝓽 𝓬𝓸𝓶𝓮 𝓽𝓸 𝓪 𝓱𝓪𝓵𝓽 𝔀𝓱𝓮𝓷 𝓽𝓱𝓲𝓷𝓰𝓼 𝓰𝓸 𝔀𝓻𝓸𝓷𝓰. 📋 𝓦𝓱𝓪𝓽 𝓘𝓼𝓼𝓾𝓮𝓼 𝓒𝓪𝓷 24/7 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓗𝓮𝓵𝓹 𝓦𝓲𝓽𝓱? 𝓗𝓮𝓻𝓮 𝓲𝓼 𝓪 𝓵𝓲𝓼𝓽 𝓸𝓯 𝓽𝓱𝓮 𝓶𝓸𝓼𝓽 𝓬𝓸𝓶𝓶𝓸𝓷 𝓹𝓻𝓸𝓫𝓵𝓮𝓶𝓼 𝓽𝓱𝓪𝓽 𝓾𝓼𝓮𝓻𝓼 𝓬𝓸𝓷𝓽𝓪𝓬𝓽 𝓵𝓲𝓿𝓮 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓽𝓸 𝓼𝓸𝓵𝓿𝓮: ❌ 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓻𝓻𝓸𝓻 𝓒𝓸𝓭𝓮𝓼 • 𝓗202, 6000 𝓼𝓮𝓻𝓲𝓮𝓼, 6123, 3371, 𝓪𝓷𝓭 𝓸𝓽𝓱𝓮𝓻𝓼 𝓬𝓪𝓷 𝓹𝓻𝓮𝓿𝓮𝓷𝓽 𝓪𝓬𝓬𝓮𝓼𝓼 𝓽𝓸 𝔂𝓸𝓾𝓻 𝓬𝓸𝓶𝓹𝓪𝓷𝔂 𝓯𝓲𝓵𝓮 𝓸𝓻 𝓷𝓮𝓽𝔀𝓸𝓻𝓴. 💾 𝓒𝓸𝓶𝓹𝓪𝓷𝔂 𝓕𝓲𝓵𝓮 𝓘𝓼𝓼𝓾𝓮𝓼 • 𝓕𝓲𝓵𝓮 𝓷𝓸𝓽 𝓸𝓹𝓮𝓷𝓲𝓷𝓰? 𝓒𝓸𝓻𝓻𝓾𝓹𝓽𝓮𝓭 𝓭𝓪𝓽𝓪? 𝓜𝓲𝓼𝓼𝓲𝓷𝓰 𝓮𝓷𝓽𝓻𝓲𝓮𝓼? 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓬𝓪𝓷 𝓱𝓮𝓵𝓹 𝓻𝓮𝓼𝓽𝓸𝓻𝓮 𝓸𝓻 𝓻𝓮𝓹𝓪𝓲𝓻 𝔂𝓸𝓾𝓻 𝓬𝓸𝓶𝓹𝓪𝓷𝔂 𝓯𝓲𝓵𝓮. 🧾 𝓟𝓪𝔂𝓻𝓸𝓵𝓵 & 𝓣𝓪𝔁 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓐𝓼𝓼𝓲𝓼𝓽𝓪𝓷𝓬𝓮 𝔀𝓲𝓽𝓱 𝓹𝓪𝔂𝓻𝓸𝓵𝓵 𝓹𝓻𝓸𝓬𝓮𝓼𝓼𝓲𝓷𝓰, 𝓦-2 𝓯𝓸𝓻𝓶𝓼, 𝓭𝓲𝓻𝓮𝓬𝓽 𝓭𝓮𝓹𝓸𝓼𝓲𝓽 𝓮𝓻𝓻𝓸𝓻𝓼, 𝓲𝓷𝓬𝓸𝓻𝓻𝓮𝓬𝓽 𝓽𝓪𝔁 𝓽𝓪𝓫𝓵𝓮𝓼, 𝓪𝓷𝓭 𝓯𝓲𝓵𝓲𝓷𝓰. 🔧 𝓘𝓷𝓼𝓽𝓪𝓵𝓵𝓪𝓽𝓲𝓸𝓷 & 𝓢𝓮𝓽𝓾𝓹 • 𝓜𝓾𝓵𝓽𝓲-𝓾𝓼𝓮𝓻 𝓼𝓮𝓽𝓾𝓹 𝓸𝓷 𝓼𝓮𝓻𝓿𝓮𝓻𝓼, 𝓬𝓾𝓼𝓽𝓸𝓶 𝓬𝓸𝓷𝓯𝓲𝓰𝓾𝓻𝓪𝓽𝓲𝓸𝓷, 𝓱𝓸𝓼𝓽𝓲𝓷𝓰 𝓶𝓲𝓰𝓻𝓪𝓽𝓲𝓸𝓷, 𝓸𝓻 𝓿𝓮𝓻𝓼𝓲𝓸𝓷 𝓾𝓹𝓰𝓻𝓪𝓭𝓮𝓼. 📊 𝓡𝓮𝓹𝓸𝓻𝓽𝓲𝓷𝓰 & 𝓘𝓷𝓿𝓮𝓷𝓽𝓸𝓻𝔂 𝓔𝓻𝓻𝓸𝓻𝓼 • 𝓣𝓻𝓸𝓾𝓫𝓵𝓮𝓼𝓱𝓸𝓸𝓽𝓲𝓷𝓰 𝓲𝓷𝓬𝓸𝓻𝓻𝓮𝓬𝓽 𝓻𝓮𝓹𝓸𝓻𝓽𝓼, 𝓲𝓷𝓿𝓮𝓷𝓽𝓸𝓻𝔂 𝓽𝓻𝓪𝓬𝓴𝓲𝓷𝓰 𝓮𝓻𝓻𝓸𝓻𝓼, 𝓸𝓻 𝓐𝓭𝓿𝓪𝓷𝓬𝓮𝓭 𝓡𝓮𝓹𝓸𝓻𝓽𝓲𝓷𝓰 𝓲𝓼𝓼𝓾𝓮𝓼. 🌐 𝓒𝓵𝓸𝓾𝓭 𝓗𝓸𝓼𝓽𝓲𝓷𝓰 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓟𝓻𝓸𝓫𝓵𝓮𝓶𝓼 𝓪𝓬𝓬𝓮𝓼𝓼𝓲𝓷𝓰 𝓱𝓸𝓼𝓽𝓮𝓭 𝓯𝓲𝓵𝓮𝓼 𝓸𝓻 𝓼𝔂𝓷𝓬𝓲𝓷𝓰 𝓲𝓼𝓼𝓾𝓮𝓼 𝓫𝓮𝓽𝔀𝓮𝓮𝓷 𝓾𝓼𝓮𝓻𝓼. 💡 𝓦𝓱𝓪𝓽 𝓽𝓸 𝓔𝔁𝓹𝓮𝓬𝓽 𝓦𝓱𝓮𝓷 𝓨𝓸𝓾 𝓒𝓪𝓵𝓵 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓦𝓱𝓮𝓷 𝔂𝓸𝓾 𝓭𝓲𝓪𝓵 1-855-219-0007, 𝔂𝓸𝓾 𝓪𝓻𝓮 𝓬𝓸𝓷𝓷𝓮𝓬𝓽𝓮𝓭 𝔀𝓲𝓽𝓱 𝓪 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓼𝓹𝓮𝓬𝓲𝓪𝓵𝓲𝓼𝓽 𝓽𝓻𝓪𝓲𝓷𝓮𝓭 𝓽𝓸 𝓼𝓸𝓵𝓿𝓮 𝓲𝓼𝓼𝓾𝓮𝓼 𝓮𝓯𝓯𝓲𝓬𝓲𝓮𝓷𝓽𝓵𝔂 𝓪𝓷𝓭 𝓹𝓻𝓸𝓯𝓮𝓼𝓼𝓲𝓸𝓷𝓪𝓵𝓵𝔂. 𝓗𝓮𝓻𝓮 𝓲𝓼 𝔀𝓱𝓪𝓽 𝔂𝓸𝓾 𝓬𝓪𝓷 𝓮𝔁𝓹𝓮𝓬𝓽 𝓭𝓾𝓻𝓲𝓷𝓰 𝔂𝓸𝓾𝓻 𝓬𝓪𝓵𝓵: 1. 𝓟𝓻𝓸𝓶𝓹𝓽, 24/7 𝓪𝓬𝓬𝓮𝓼𝓼 – 𝓝𝓸 𝔀𝓪𝓲𝓽𝓲𝓷𝓰 𝓾𝓷𝓽𝓲𝓵 𝓫𝓾𝓼𝓲𝓷𝓮𝓼𝓼 𝓱𝓸𝓾𝓻𝓼 2. 𝓒𝓮𝓻𝓽𝓲𝓯𝓲𝓮𝓭 𝓮𝔁𝓹𝓮𝓻𝓽𝓼 – 𝓦𝓲𝓽𝓱 𝓭𝓮𝓮𝓹 𝓴𝓷𝓸𝔀𝓵𝓮𝓭𝓰𝓮 𝓸𝓯 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓯𝓮𝓪𝓽𝓾𝓻𝓮𝓼 3. 𝓟𝓮𝓻𝓼𝓸𝓷𝓪𝓵𝓲𝔃𝓮𝓭 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 – 𝓑𝓪𝓼𝓮𝓭 𝓸𝓷 𝔂𝓸𝓾𝓻 𝓿𝓮𝓻𝓼𝓲𝓸𝓷, 𝓼𝓮𝓽𝓾𝓹, 𝓪𝓷𝓭 𝓲𝓷𝓭𝓾𝓼𝓽𝓻𝔂 4. 𝓢𝓽𝓮𝓹-𝓫𝔂-𝓼𝓽𝓮𝓹 𝓰𝓾𝓲𝓭𝓪𝓷𝓬𝓮 – 𝓞𝓿𝓮𝓻 𝓹𝓱𝓸𝓷𝓮 𝓸𝓻 𝓻𝓮𝓶𝓸𝓽𝓮 𝓪𝓬𝓬𝓮𝓼𝓼 𝓼𝓮𝓼𝓼𝓲𝓸𝓷𝓼 5. 𝓓𝓪𝓽𝓪 𝓹𝓻𝓸𝓽𝓮𝓬𝓽𝓲𝓸𝓷 & 𝓬𝓸𝓷𝓯𝓲𝓭𝓮𝓷𝓽𝓲𝓪𝓵𝓲𝓽𝔂 – 𝓨𝓸𝓾𝓻 𝓯𝓲𝓵𝓮𝓼 𝓪𝓷𝓭 𝓭𝓮𝓽𝓪𝓲𝓵𝓼 𝓼𝓽𝓪𝔂 𝓼𝓮𝓬𝓾𝓻𝓮 ________________________________________ 📞 𝓒𝓸𝓷𝓽𝓪𝓬𝓽 𝓜𝓮𝓽𝓱𝓸𝓭𝓼: 𝓞𝓯𝓯𝓲𝓬𝓲𝓪𝓵 & 𝓥𝓮𝓻𝓲𝓯𝓲𝓮𝓭 𝓒𝓱𝓪𝓷𝓷𝓮𝓵𝓼 𝓨𝓸𝓾 𝓬𝓪𝓷 𝓻𝓮𝓪𝓬𝓱 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓽𝓱𝓻𝓸𝓾𝓰𝓱 𝓼𝓮𝓿𝓮𝓻𝓪𝓵 𝓵𝓮𝓰𝓲𝓽𝓲𝓶𝓪𝓽𝓮 𝓶𝓮𝓽𝓱𝓸𝓭𝓼, 𝓭𝓮𝓹𝓮𝓷𝓭𝓲𝓷𝓰 𝓸𝓷 𝔂𝓸𝓾𝓻 𝓹𝓻𝓮𝓯𝓮𝓻𝓮𝓷𝓬𝓮: ✅ 1. 𝓟𝓱𝓸𝓷𝓮 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 – 📞 1-855-219-0007 𝓘𝓭𝓮𝓪𝓵 𝓯𝓸𝓻 𝓲𝓶𝓶𝓮𝓭𝓲𝓪𝓽𝓮 𝓲𝓼𝓼𝓾𝓮𝓼 𝓽𝓱𝓪𝓽 𝓷𝓮𝓮𝓭 𝓺𝓾𝓲𝓬𝓴 𝓻𝓮𝓼𝓸𝓵𝓾𝓽𝓲𝓸𝓷 — 𝓭𝓪𝔂 𝓸𝓻 𝓷𝓲𝓰𝓱𝓽. ✅ 2. 𝓘𝓷-𝓟𝓻𝓸𝓭𝓾𝓬𝓽 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓞𝓹𝓮𝓷 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 • 𝓖𝓸 𝓽𝓸 𝓗𝓮𝓵𝓹 > 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓓𝓮𝓼𝓴𝓽𝓸𝓹 𝓗𝓮𝓵𝓹 > 𝓒𝓸𝓷𝓽𝓪𝓬𝓽 𝓤𝓼 • 𝓢𝓮𝓵𝓮𝓬𝓽 𝔂𝓸𝓾𝓻 𝓲𝓼𝓼𝓾𝓮 𝓪𝓷𝓭 𝓬𝓱𝓸𝓸𝓼𝓮 𝓒𝓱𝓪𝓽 𝓸𝓻 𝓒𝓪𝓵𝓵𝓫𝓪𝓬𝓴 ✅ 3. 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓦𝓮𝓫𝓼𝓲𝓽𝓮 𝓥𝓲𝓼𝓲𝓽 𝓽𝓱𝓮 𝓸𝓯𝓯𝓲𝓬𝓲𝓪𝓵 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝔀𝓮𝓫𝓼𝓲𝓽𝓮 𝓢𝓮𝓪𝓻𝓬𝓱 𝓫𝔂 𝓽𝓸𝓹𝓲𝓬 𝓸𝓻 𝓹𝓻𝓸𝓭𝓾𝓬𝓽 𝓪𝓷𝓭 𝓬𝓸𝓷𝓷𝓮𝓬𝓽 𝔀𝓲𝓽𝓱 𝓪 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓻𝓮𝓹 𝓽𝓱𝓻𝓸𝓾𝓰𝓱 𝓬𝓱𝓪𝓽 𝓸𝓻 𝓬𝓸𝓶𝓶𝓾𝓷𝓲𝓽𝔂 𝓯𝓸𝓻𝓾𝓶𝓼. ✅ 4. 𝓒𝓮𝓻𝓽𝓲𝓯𝓲𝓮𝓭 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓟𝓻𝓸𝓐𝓭𝓿𝓲𝓼𝓸𝓻𝓼 𝓟𝓻𝓸𝓐𝓭𝓿𝓲𝓼𝓸𝓻𝓼 𝓪𝓻𝓮 𝓪𝓬𝓬𝓸𝓾𝓷𝓽𝓲𝓷𝓰 𝓪𝓷𝓭 𝓽𝓮𝓬𝓱 𝓹𝓻𝓸𝓯𝓮𝓼𝓼𝓲𝓸𝓷𝓪𝓵𝓼 𝓽𝓻𝓪𝓲𝓷𝓮𝓭 𝓪𝓷𝓭 𝓬𝓮𝓻𝓽𝓲𝓯𝓲𝓮𝓭 𝓫𝔂 𝓘𝓷𝓽𝓾𝓲𝓽. 𝓕𝓲𝓷𝓭 𝓸𝓷𝓮 𝓱𝓮𝓻𝓮: 🔗 𝓱𝓽𝓽𝓹𝓼://𝓺𝓾𝓲𝓬𝓴𝓫𝓸𝓸𝓴𝓼.𝓲𝓷𝓽𝓾𝓲𝓽.𝓬𝓸𝓶/𝓯𝓲𝓷𝓭-𝓪𝓷-𝓪𝓬𝓬𝓸𝓾𝓷𝓽𝓪𝓷𝓽/ 🧑💻 𝓑𝓮𝓷𝓮𝓯𝓲𝓽𝓼 𝓸𝓯 24/7 𝓛𝓲𝓿𝓮 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓗𝓮𝓻𝓮’𝓼 𝓱𝓸𝔀 24/7 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓰𝓲𝓿𝓮𝓼 𝔂𝓸𝓾𝓻 𝓫𝓾𝓼𝓲𝓷𝓮𝓼𝓼 𝓪𝓷 𝓮𝓭𝓰𝓮: • ✅ 𝓝𝓸 𝓓𝓸𝔀𝓷𝓽𝓲𝓶𝓮: 𝓢𝓸𝓵𝓿𝓮 𝓲𝓼𝓼𝓾𝓮𝓼 𝔀𝓱𝓮𝓷 𝓽𝓱𝓮𝔂 𝓱𝓪𝓹𝓹𝓮𝓷 — 𝓷𝓸𝓽 𝔀𝓱𝓮𝓷 𝓸𝓯𝓯𝓲𝓬𝓮𝓼 𝓸𝓹𝓮𝓷 • ✅ 𝓖𝓵𝓸𝓫𝓪𝓵 𝓐𝓬𝓬𝓮𝓼𝓼: 𝓝𝓸 𝓶𝓪𝓽𝓽𝓮𝓻 𝔂𝓸𝓾𝓻 𝓽𝓲𝓶𝓮 𝔃𝓸𝓷𝓮, 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓲𝓼 𝓪𝓿𝓪𝓲𝓵𝓪𝓫𝓵𝓮 • ✅ 𝓔𝔁𝓹𝓮𝓻𝓽 𝓣𝓻𝓸𝓾𝓫𝓵𝓮𝓼𝓱𝓸𝓸𝓽𝓲𝓷𝓰: 𝓖𝓮𝓽 𝓻𝓲𝓰𝓱𝓽 𝓽𝓸 𝓽𝓱𝓮 𝓼𝓸𝓵𝓾𝓽𝓲𝓸𝓷 𝔀𝓲𝓽𝓱 𝓽𝓻𝓪𝓲𝓷𝓮𝓭 𝓹𝓻𝓸𝓯𝓮𝓼𝓼𝓲𝓸𝓷𝓪𝓵𝓼 • ✅ 𝓟𝓮𝓪𝓬𝓮 𝓸𝓯 𝓜𝓲𝓷𝓭: 𝓨𝓸𝓾𝓻 𝓪𝓬𝓬𝓸𝓾𝓷𝓽𝓲𝓷𝓰 𝓭𝓪𝓽𝓪 𝓪𝓷𝓭 𝔀𝓸𝓻𝓴𝓯𝓵𝓸𝔀 𝓼𝓽𝓪𝔂 𝓼𝓮𝓬𝓾𝓻𝓮 🧰 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓯𝓸𝓻 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓥𝓮𝓻𝓼𝓲𝓸𝓷𝓼 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓲𝓼 𝓪𝓿𝓪𝓲𝓵𝓪𝓫𝓵𝓮 𝓯𝓸𝓻 𝓪𝓵𝓵 𝓶𝓪𝓳𝓸𝓻 𝓿𝓮𝓻𝓼𝓲𝓸𝓷𝓼, 𝓲𝓷𝓬𝓵𝓾𝓭𝓲𝓷𝓰: • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 2025 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 2024 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 2023 𝓪𝓷𝓭 𝓮𝓪𝓻𝓵𝓲𝓮𝓻 • 𝓘𝓷𝓭𝓾𝓼𝓽𝓻𝔂 𝓔𝓭𝓲𝓽𝓲𝓸𝓷𝓼: 𝓒𝓸𝓷𝓽𝓻𝓪𝓬𝓽𝓸𝓻, 𝓝𝓸𝓷𝓹𝓻𝓸𝓯𝓲𝓽, 𝓜𝓪𝓷𝓾𝓯𝓪𝓬𝓽𝓾𝓻𝓲𝓷𝓰, 𝓦𝓱𝓸𝓵𝓮𝓼𝓪𝓵𝓮, 𝓡𝓮𝓽𝓪𝓲𝓵, 𝓪𝓷𝓭 𝓟𝓻𝓸𝓯𝓮𝓼𝓼𝓲𝓸𝓷𝓪𝓵 𝓢𝓮𝓻𝓿𝓲𝓬𝓮𝓼 𝓦𝓱𝓮𝓽𝓱𝓮𝓻 𝔂𝓸𝓾 𝓪𝓻𝓮 𝓻𝓾𝓷𝓷𝓲𝓷𝓰 𝔂𝓸𝓾𝓻 𝓫𝓾𝓼𝓲𝓷𝓮𝓼𝓼 𝓸𝓷 𝓪 𝓵𝓸𝓬𝓪𝓵 𝓼𝓮𝓻𝓿𝓮𝓻 𝓸𝓻 𝓾𝓼𝓲𝓷𝓰 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝔀𝓲𝓽𝓱 𝓗𝓸𝓼𝓽𝓲𝓷𝓰, 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓪𝓰𝓮𝓷𝓽𝓼 𝓬𝓪𝓷 𝓱𝓪𝓷𝓭𝓵𝓮 𝔂𝓸𝓾𝓻 𝓬𝓸𝓷𝓯𝓲𝓰𝓾𝓻𝓪𝓽𝓲𝓸𝓷. 🛡️ 𝓢𝓮𝓬𝓾𝓻𝓲𝓽𝔂 𝓣𝓲𝓹𝓼 𝓦𝓱𝓮𝓷 𝓒𝓪𝓵𝓵𝓲𝓷𝓰 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓦𝓱𝓮𝓷 𝓬𝓪𝓵𝓵𝓲𝓷𝓰 𝓪𝓷𝔂 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓵𝓲𝓷𝓮, 𝓯𝓸𝓵𝓵𝓸𝔀 𝓽𝓱𝓮𝓼𝓮 𝓫𝓮𝓼𝓽 𝓹𝓻𝓪𝓬𝓽𝓲𝓬𝓮𝓼 𝓽𝓸 𝓼𝓽𝓪𝔂 𝓼𝓪𝓯𝓮: • 🔒 𝓝𝓮𝓿𝓮𝓻 𝓼𝓱𝓪𝓻𝓮 𝔂𝓸𝓾𝓻 𝓯𝓾𝓵𝓵 𝓼𝓸𝓬𝓲𝓪𝓵 𝓼𝓮𝓬𝓾𝓻𝓲𝓽𝔂 𝓷𝓾𝓶𝓫𝓮𝓻 𝓸𝓻 𝓫𝓪𝓷𝓴𝓲𝓷𝓰 𝓹𝓪𝓼𝓼𝔀𝓸𝓻𝓭𝓼 • 💼 𝓗𝓪𝓿𝓮 𝔂𝓸𝓾𝓻 𝓵𝓲𝓬𝓮𝓷𝓼𝓮/𝓹𝓻𝓸𝓭𝓾𝓬𝓽 𝓷𝓾𝓶𝓫𝓮𝓻 𝓻𝓮𝓪𝓭𝔂 • 🖥️ 𝓤𝓼𝓮 𝓻𝓮𝓶𝓸𝓽𝓮 𝓪𝓬𝓬𝓮𝓼𝓼 𝓸𝓷𝓵𝔂 𝔀𝓲𝓽𝓱 𝓿𝓮𝓻𝓲𝓯𝓲𝓮𝓭 𝓽𝓮𝓬𝓱𝓷𝓲𝓬𝓲𝓪𝓷𝓼 • 📧 𝓒𝓸𝓷𝓯𝓲𝓻𝓶 𝓯𝓸𝓵𝓵𝓸𝔀-𝓾𝓹 𝓮𝓶𝓪𝓲𝓵𝓼 𝓬𝓸𝓶𝓮 𝓯𝓻𝓸𝓶 𝓸𝓯𝓯𝓲𝓬𝓲𝓪𝓵 𝓭𝓸𝓶𝓪𝓲𝓷𝓼 (𝓮.𝓰., @𝓲𝓷𝓽𝓾𝓲𝓽.𝓬𝓸𝓶) 𝓘𝓯 𝔂𝓸𝓾 𝓪𝓻𝓮 𝓾𝓼𝓲𝓷𝓰 𝓽𝓱𝓲𝓻𝓭-𝓹𝓪𝓻𝓽𝔂 𝓼𝓾𝓹𝓹𝓸𝓻𝓽, 𝓮𝓷𝓼𝓾𝓻𝓮 𝓽𝓱𝓮 𝓹𝓻𝓸𝓿𝓲𝓭𝓮𝓻 𝓲𝓼 𝓪𝓾𝓽𝓱𝓸𝓻𝓲𝔃𝓮𝓭 𝓪𝓷𝓭 𝓱𝓪𝓼 𝓼𝓮𝓬𝓾𝓻𝓮 𝓹𝓻𝓸𝓽𝓸𝓬𝓸𝓵𝓼 𝓲𝓷 𝓹𝓵𝓪𝓬𝓮 𝓯𝓸𝓻 𝓭𝓪𝓽𝓪 𝓹𝓻𝓸𝓽𝓮𝓬𝓽𝓲𝓸𝓷. 📌 𝓗𝓸𝔀 𝓽𝓸 𝓟𝓻𝓮𝓹𝓪𝓻𝓮 𝓑𝓮𝓯𝓸𝓻𝓮 𝓨𝓸𝓾 𝓒𝓪𝓵𝓵 𝓣𝓸 𝓱𝓮𝓵𝓹 𝓻𝓮𝓼𝓸𝓵𝓿𝓮 𝔂𝓸𝓾𝓻 𝓲𝓼𝓼𝓾𝓮 𝓯𝓪𝓼𝓽𝓮𝓻, 𝓱𝓪𝓿𝓮 𝓽𝓱𝓮 𝓯𝓸𝓵𝓵𝓸𝔀𝓲𝓷𝓰 𝓻𝓮𝓪𝓭𝔂: • 𝓨𝓸𝓾𝓻 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓿𝓮𝓻𝓼𝓲𝓸𝓷 (𝓮.𝓰., 2024, 𝓓𝓮𝓼𝓴𝓽𝓸𝓹, 𝓒𝓵𝓸𝓾𝓭-𝓱𝓸𝓼𝓽𝓮𝓭, 𝓮𝓽𝓬.) • 𝓓𝓮𝓼𝓬𝓻𝓲𝓹𝓽𝓲𝓸𝓷 𝓸𝓯 𝓽𝓱𝓮 𝓲𝓼𝓼𝓾𝓮 𝓸𝓻 𝓮𝓻𝓻𝓸𝓻 𝓶𝓮𝓼𝓼𝓪𝓰𝓮 • 𝓨𝓸𝓾𝓻 𝓫𝓾𝓼𝓲𝓷𝓮𝓼𝓼 𝓷𝓪𝓶𝓮 𝓪𝓷𝓭 𝓷𝓾𝓶𝓫𝓮𝓻 𝓸𝓯 𝓾𝓼𝓮𝓻𝓼 • 𝓘𝓷𝓽𝓮𝓻𝓷𝓮𝓽 𝓬𝓸𝓷𝓷𝓮𝓬𝓽𝓲𝓸𝓷 𝓼𝓽𝓪𝓽𝓾𝓼 (𝓯𝓸𝓻 𝓱𝓸𝓼𝓽𝓮𝓭 𝓾𝓼𝓮𝓻𝓼) • 𝓐𝓷𝔂 𝓻𝓮𝓬𝓮𝓷𝓽 𝓬𝓱𝓪𝓷𝓰𝓮𝓼 𝓶𝓪𝓭𝓮 𝓫𝓮𝓯𝓸𝓻𝓮 𝓽𝓱𝓮 𝓲𝓼𝓼𝓾𝓮 𝓼𝓽𝓪𝓻𝓽𝓮𝓭 🌍 𝓘𝓷𝓽𝓮𝓻𝓷𝓪𝓽𝓲𝓸𝓷𝓪𝓵 𝓢𝓾𝓹𝓹𝓸𝓻𝓽 𝓐𝓿𝓪𝓲𝓵𝓪𝓫𝓲𝓵𝓲𝓽𝔂 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓲𝓼 𝓾𝓼𝓮𝓭 𝓰𝓵𝓸𝓫𝓪𝓵𝓵𝔂. 𝓦𝓱𝓲𝓵𝓮 𝓽𝓱𝓮 𝓤.𝓢. 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓵𝓲𝓷𝓮 𝓲𝓼 𝓸𝓯𝓽𝓮𝓷 𝓽𝓸𝓵𝓵-𝓯𝓻𝓮𝓮, 𝓾𝓼𝓮𝓻𝓼 𝓯𝓻𝓸𝓶 𝓒𝓪𝓷𝓪𝓭𝓪, 𝓤𝓚, 𝓘𝓷𝓭𝓲𝓪, 𝓪𝓷𝓭 𝓐𝓾𝓼𝓽𝓻𝓪𝓵𝓲𝓪 𝓶𝓪𝔂 𝓱𝓪𝓿𝓮 𝓵𝓸𝓬𝓪𝓵 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓸𝓹𝓽𝓲𝓸𝓷𝓼. 𝓒𝓱𝓮𝓬𝓴 𝔂𝓸𝓾𝓻 𝓻𝓮𝓰𝓲𝓸𝓷’𝓼 𝓘𝓷𝓽𝓾𝓲𝓽 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓼𝓲𝓽𝓮 𝓯𝓸𝓻 𝓶𝓸𝓻𝓮. 🏁 𝓒𝓸𝓷𝓬𝓵𝓾𝓼𝓲𝓸𝓷: 𝓓𝓸 𝓷𝓸𝓽 𝓛𝓮𝓽 𝓣𝓮𝓬𝓱 𝓟𝓻𝓸𝓫𝓵𝓮𝓶𝓼 𝓢𝓵𝓸𝔀 𝓨𝓸𝓾 𝓓𝓸𝔀𝓷 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓔𝓷𝓽𝓮𝓻𝓹𝓻𝓲𝓼𝓮 𝓲𝓼 𝓪 𝓻𝓸𝓫𝓾𝓼𝓽 𝓹𝓵𝓪𝓽𝓯𝓸𝓻𝓶 𝓭𝓮𝓼𝓲𝓰𝓷𝓮𝓭 𝓯𝓸𝓻 𝓰𝓻𝓸𝔀𝓽𝓱 — 𝓫𝓾𝓽 𝓮𝓿𝓮𝓷 𝓽𝓱𝓮 𝓫𝓮𝓼𝓽 𝓼𝔂𝓼𝓽𝓮𝓶𝓼 𝓷𝓮𝓮𝓭 𝓼𝓾𝓹𝓹𝓸𝓻𝓽. 𝓕𝓻𝓸𝓶 𝓭𝓪𝓽𝓪 𝓯𝓲𝓵𝓮 𝓲𝓼𝓼𝓾𝓮𝓼 𝓽𝓸 𝓪𝓭𝓿𝓪𝓷𝓬𝓮𝓭 𝓻𝓮𝓹𝓸𝓻𝓽𝓲𝓷𝓰 𝓺𝓾𝓮𝓼𝓽𝓲𝓸𝓷𝓼, 24/7 𝓵𝓲𝓿𝓮 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓮𝓷𝓼𝓾𝓻𝓮𝓼 𝔂𝓸𝓾 𝓪𝓻𝓮 𝓪𝓬𝓬𝓸𝓾𝓷𝓽𝓲𝓷𝓰 𝓷𝓮𝓿𝓮𝓻 𝓶𝓲𝓼𝓼𝓮𝓼 𝓪 𝓫𝓮𝓪𝓽. 📞 𝓒𝓪𝓵𝓵 𝓷𝓸𝔀: 1-855-219-0007 💬 𝓖𝓮𝓽 𝓱𝓮𝓵𝓹 𝔀𝓲𝓽𝓱 𝓲𝓷𝓼𝓽𝓪𝓵𝓵𝓪𝓽𝓲𝓸𝓷, 𝓹𝓪𝔂𝓻𝓸𝓵𝓵, 𝓽𝓻𝓸𝓾𝓫𝓵𝓮𝓼𝓱𝓸𝓸𝓽𝓲𝓷𝓰, 𝓪𝓷𝓭 𝓶𝓸𝓻𝓮 — 𝓪𝓷𝔂𝓽𝓲𝓶𝓮, 𝓪𝓷𝔂𝔀𝓱𝓮𝓻𝓮. 𝓦𝓱𝓮𝓽𝓱𝓮𝓻 𝔂𝓸𝓾 𝓪𝓻𝓮 𝓪 𝓼𝓶𝓪𝓵𝓵 𝓫𝓾𝓼𝓲𝓷𝓮𝓼𝓼 𝓸𝔀𝓷𝓮𝓻 𝔀𝓸𝓻𝓴𝓲𝓷𝓰 𝓵𝓪𝓽𝓮 𝓸𝓻 𝓪 𝓯𝓲𝓷𝓪𝓷𝓬𝓮 𝓶𝓪𝓷𝓪𝓰𝓮𝓻 𝓹𝓻𝓮𝓹𝓪𝓻𝓲𝓷𝓰 𝓻𝓮𝓹𝓸𝓻𝓽𝓼 𝓫𝓮𝓯𝓸𝓻𝓮 𝓼𝓾𝓷𝓻𝓲𝓼𝓮, 𝓱𝓮𝓵𝓹 𝓲𝓼 𝓳𝓾𝓼𝓽 𝓪 𝓹𝓱𝓸𝓷𝓮 𝓬𝓪𝓵𝓵 𝓪𝔀𝓪𝔂. • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓱𝓮𝓵𝓹𝓵𝓲𝓷𝓮 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓬𝓸𝓷𝓽𝓪𝓬𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓬𝓾𝓼𝓽𝓸𝓶𝓮𝓻 𝓬𝓪𝓻𝓮 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓹𝓱𝓸𝓷𝓮 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓮𝓶𝓪𝓲𝓵 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓵𝓲𝓿𝓮 𝓬𝓱𝓪𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓱𝓮𝓵𝓹 𝓭𝓮𝓼𝓴 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓬𝓸𝓷𝓽𝓪𝓬𝓽 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓽𝓮𝓪𝓶 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓬𝓾𝓼𝓽𝓸𝓶𝓮𝓻 𝓪𝓼𝓼𝓲𝓼𝓽𝓪𝓷𝓬𝓮 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓼𝓮𝓻𝓿𝓲𝓬𝓮 𝓱𝓸𝓽𝓵𝓲𝓷𝓮 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓽𝓮𝓬𝓱𝓷𝓲𝓬𝓪𝓵 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓲𝓼𝓼𝓾𝓮 𝓻𝓮𝓼𝓸𝓵𝓾𝓽𝓲𝓸𝓷 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓪𝓬𝓬𝓸𝓾𝓷𝓽 𝓱𝓮𝓵𝓹 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓹𝓪𝔂𝓶𝓮𝓷𝓽 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝔀𝓲𝓽𝓱𝓭𝓻𝓪𝔀𝓪𝓵 𝓲𝓼𝓼𝓾𝓮𝓼 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓵𝓸𝓰𝓲𝓷 𝓱𝓮𝓵𝓹 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓿𝓮𝓻𝓲𝓯𝓲𝓬𝓪𝓽𝓲𝓸𝓷 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓪𝓬𝓬𝓸𝓾𝓷𝓽 𝓻𝓮𝓬𝓸𝓿𝓮𝓻𝔂 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓵𝓸𝓼𝓽 𝓪𝓬𝓬𝓮𝓼𝓼 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓼𝓮𝓬𝓾𝓻𝓲𝓽𝔂 𝓲𝓼𝓼𝓾𝓮𝓼 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓯𝓻𝓪𝓾𝓭 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓫𝓲𝓵𝓵𝓲𝓷𝓰 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓽𝓻𝓪𝓷𝓼𝓪𝓬𝓽𝓲𝓸𝓷 𝓹𝓻𝓸𝓫𝓵𝓮𝓶𝓼 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝔀𝓪𝓵𝓵𝓮𝓽 𝓲𝓼𝓼𝓾𝓮𝓼 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓶𝓸𝓫𝓲𝓵𝓮 𝓪𝓹𝓹 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓬𝓻𝔂𝓹𝓽𝓸 𝓽𝓻𝓪𝓷𝓼𝓯𝓮𝓻 𝓱𝓮𝓵𝓹 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓮𝓻𝓻𝓸𝓻 𝓯𝓲𝔁𝓲𝓷𝓰 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓵𝓸𝓰𝓲𝓷 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓹𝓻𝓸𝓫𝓵𝓮𝓶 𝓻𝓮𝓼𝓸𝓵𝓾𝓽𝓲𝓸𝓷 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓯𝓮𝓮𝓭𝓫𝓪𝓬𝓴 𝓬𝓸𝓷𝓽𝓪𝓬𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓪𝓬𝓬𝓸𝓾𝓷𝓽 𝓼𝓾𝓼𝓹𝓮𝓷𝓼𝓲𝓸𝓷 𝓱𝓮𝓵𝓹 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝔀𝓲𝓽𝓱𝓭𝓻𝓪𝔀𝓪𝓵 𝓭𝓮𝓵𝓪𝔂 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓭𝓮𝓹𝓸𝓼𝓲𝓽 𝓲𝓼𝓼𝓾𝓮𝓼 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓬𝓻𝔂𝓹𝓽𝓸 𝓬𝓸𝓷𝓿𝓮𝓻𝓼𝓲𝓸𝓷 𝓱𝓮𝓵𝓹 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓸𝓻𝓭𝓮𝓻 𝓼𝓽𝓪𝓽𝓾𝓼 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓻𝓮𝓯𝓾𝓷𝓭 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓽𝓪𝔁 𝓭𝓸𝓬𝓾𝓶𝓮𝓷𝓽 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓲𝓷𝓽𝓮𝓻𝓷𝓪𝓽𝓲𝓸𝓷𝓪𝓵 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 24/7 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓪𝓬𝓬𝓸𝓾𝓷𝓽 𝓼𝓮𝓽𝓽𝓲𝓷𝓰𝓼 𝓱𝓮𝓵𝓹 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓹𝓪𝓼𝓼𝔀𝓸𝓻𝓭 𝓻𝓮𝓼𝓮𝓽 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓽𝔀𝓸-𝓯𝓪𝓬𝓽𝓸𝓻 𝓪𝓾𝓽𝓱𝓮𝓷𝓽𝓲𝓬𝓪𝓽𝓲𝓸𝓷 𝓱𝓮𝓵𝓹 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓬𝓾𝓼𝓽𝓸𝓶𝓮𝓻 𝓲𝓷𝓺𝓾𝓲𝓻𝔂 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓼𝓾𝓹𝓹𝓸𝓻𝓽 𝓷𝓾𝓶𝓫𝓮𝓻 𝓤𝓢𝓐 • 𝓠𝓾𝓲𝓬𝓴𝓑𝓸𝓸𝓴𝓼 𝓱𝓮𝓵𝓹 𝓬𝓮𝓷𝓽𝓮𝓻 𝓹𝓱𝓸𝓷𝓮 𝓷𝓾𝓶𝓫𝓮𝓻
I am excited to join this community to learn the more particularly the Matlab/Simulink
I just learned you can access MATLAB Online from the following shortcut in your web browser: https://matlab.new
Thanks @Yann Debray
From his recent blog post: pip & uv in MATLAB Online » Artificial Intelligence - MATLAB & Simulink
I'm developing a comprehensive MATLAB programming course and seeking passionate co-trainers to collaborate!
Why MATLAB Matters:Many people underestimate MATLAB's significance in:
- Communication systems
- Signal processing
- Mathematical modeling
- Engineering applications
- Scientific computing
Course Structure:
- Foundation Module: MATLAB basics and fundamentals
- Image Processing: Practical applications and techniques
- Signal Processing: Analysis and implementation
- Machine Learning: ML algorithms using MATLAB
- Hands-on Learning: Projects, assignments.
What I'm Looking For:
- Enthusiastic educators willing to share knowledge
- Experience in any MATLAB application area
- Commitment to collaborative teaching
Interested in joining as a co-trainer? Please comment below or reach out directly!
Online Doc + System Browser
15%
Online Doc + Dedicated Browser
15%
Offline Doc +System Browser
5%
Offline Doc + Dedicated Browser
20%
Hybrid Approach (Support All Modes)
25%
User-Definable / Fully Configurable
20%
20 votes
I'm working on training neural networks without backpropagation / automatic differentiation, using locally derived analytic forms of update rules. Given that this allows a direct formula to be derived for the update rule, it removes alot of the overhead that is otherwise required from automatic differentiation.
However, matlab's functionalities for neural networks are currently solely based around backpropagation and automatic differentiation, such as the dlgradient function and requiring everything to be dlarrays during training.
I have two main requests, specifically for functions that perform a single operation within a single layer of a neural network, such as "dlconv", "fullyconnect", "maxpool", "avgpool", "relu", etc:
- these functions should also allow normal gpuArray data instead of requiring everything to be dlarrays.
- these functions are currently designed to only perform the forward pass. I request that these also be designed to perform the backward pass if user requests. There can be another input user flag that can be "forward" (default) or "backward", and then the function should have all the necessary inputs to perform that operation (e.g. for "avgpool" forward pass it only needs the avgpool input data and the avgpool parameters, but for the "avgpool" backward pass it needs the deriviative w.r.t. the avgpool output data, the avgpool parameters, and the original data dimensions). I know that there is a maxunpool function that achieves this for maxpool, but it has significant issues when trying to use it this way instead of by backpropagation in a dlgradient type layer, see (https://www.mathworks.com/matlabcentral/answers/2179587-making-a-custom-way-to-train-cnns-and-i-am-noticing-that-avgpool-is-significantly-faster-than-maxpo?s_tid=srchtitle).
I don't know how many people would benefit from this feature, and someone could always spend their time creating these functionalities themselves by matlab scripts, cuDNN mex, etc., but regardless it would be nice for matlab to have this allowable for more customizable neural net training.
I recently published this blog post about resources to help people learn MATLAB https://blogs.mathworks.com/matlab/2025/09/11/learning-matlab-in-2025/
What are your favourite MATLAB learning resources?
Edit 15 Oct 2025: Removed incorrect code. Replaced symmatrix2sym and symfunmatrix2symfun with sym and symfun respectively (latter supported as of 2024b).
The Symbolic Math Toolbox does not have its own dot and and cross functions. That's o.k. (maybe) for garden variety vectors of sym objects where those operations get shipped off to the base Matlab functions
x = sym('x',[3,1]); y = sym('y',[3,1]);
which dot(x,y)
dot(x,y)
which cross(x,y)
cross(x,y)
clearvars
x = symmatrix('x',[3,1]); y = symmatrix('y',[3,1]);
z = symmatrix('z',[1,1]);
sympref('AbbreviateOutput',false);
dot() expands the result, which isn't really desirable for exposition.
eqn = z == dot(x,y)
Also, dot() returns the the result in terms of the conjugate of x, which can't be simplifed away at the symmatrix level
assumeAlso(sym(x),'real')
class(eqn)
try
eqn = z == simplify(dot(x,y))
catch ME
ME.message
end
To get rid of the conjugate, we have to resort to sym
eqn = simplify(sym(eqn))
but again we are in expanded form, which defeats the purpose of symmatrix (et. al.)
But at least we can do this to get a nice equation
eqn = z == x.'*y
dot errors with symfunmatrix inputs
clearvars
syms t real
x = symfunmatrix('x(t)',t,[3,1]); y = symfunmatrix('y(t)',t,[3,1]);
try
dot(x,y)
catch ME
ME.message
end
Cross works (accidentally IMO) with symmatrix, but expands the result, which isn't really desirable for exposition
clearvars
x = symmatrix('x',[3,1]); y = symmatrix('y',[3,1]);
z = symmatrix('z',[3,1]);
eqn = z == cross(x,y)
And it doesn't work at all if an input is a symfunmatrix
syms t
w = symfunmatrix('w(t)',t,[3,1]);
try
eqn = z == cross(x,w);
catch ME
ME.message
end
In the latter case we can expand with
eqn = z == cross(sym(x),symfun(w)) % x has to be converted
But we can't do the same with dot (as shown above, dot doesn't like symfun inputs)
try
eqn = z == dot(sym(x),symfun(w))
catch ME
ME.message
end
Looks like the only choice for dot with symfunmatrix is to write it by hand at the matrix level
x.'*w
or at the sym/symfun level
sym(x).'*symfun(w) % assuming x is real
Ideally, I'd like to see dot and cross implemented for symmatrix and symfunmatrix types where neither function would evaluate, i.e., expand, until both arguments are subs-ed with sym or symfun objects of appropriate dimension.
Also, it would be nice if symmatrix could be assumed to be real. Is there a reason why being able to do so wouldn't make sense?
try
assume(x,'real')
catch ME
ME.message
end
What if you had no isprime utility to rely on in MATLAB? How would you identify a number as prime? An easy answer might be something tricky, like that in simpleIsPrime0.
simpleIsPrime0 = @(N) ismember(N,primes(N));
But I’ll also disallow the use of primes here, as it does not really test to see if a number is prime. As well, it would seem horribly inefficient, generating a possibly huge list of primes, merely to learn something about the last member of the list.
Looking for a more serious test for primality, I’ve already shown how to lighten the load by a bit using roughness, to sometimes identify numbers as composite and therefore not prime.
https://www.mathworks.com/matlabcentral/discussions/tips/879745-primes-and-rough-numbers-basic-ideas
But to actually learn if some number is prime, we must do a little more. Yes, this is a common homework problem assigned to students, something we have seen many times on Answers. It can be approached in many ways too, so it is worth looking at the problem in some depth.
The definition of a prime number is a natural number greater than 1, which has only two factors, thus 1 and itself. That makes a simple test for primality of the number N easy. We just try dividing the number by every integer greater than 1, and not exceeding N-1. If any of those trial divides leaves a zero remainder, then N cannot be prime. And of course we can use mod or rem instead of an explicit divide, so we need not worry about floating point trash, as long as the numbers being tested are not too large.
simpleIsPrime1 = @(N) all(mod(N,2:N-1) ~= 0);
Of course, simpleIsPrime1 is not a good code, in the sense that it fails to check if N is an integer, or if N is less than or equal to 1. It is not vectorized, and it has no documentation at all. But it does the job well enough for one simple line of code. There is some virtue in simplicity after all, and it is certainly easy to read. But sometimes, I wish a function handle could include some help comments too! A feature request might be in the offing.
simpleIsPrime1(9931)
simpleIsPrime1(9932)
simpleIsPrime1 works quite nicely, and seems pretty fast. What could be wrong? At some point, the student is given a more difficult problem, to identify if a significantly larger integer is prime. simpleIsPrime1 will then cause a computer to grind to a distressing halt if given a sufficiently large number to test. Or it might even error out, when too large a vector of numbers was generated to test against. For example, I don't think you want to test a number of the order of 2^64 using simpleIsPrime1, as performing on the order of 2^64 divides will be highly time consuming.
uint64(2)^63-25
Is it prime? I’ve not tested it to learn if it is, and simpleIsPrime1 is not the tool to perform that test anyway.
A student might realize the largest possible integer factors of some number N are the numbers N/2 and N itself. But, if N/2 is a factor, then so is 2, and some thought would suggest it is sufficient to test only for factors that do not exceed sqrt(N). This is because if a is a divisor of N, then so is b=N/a. If one of them is larger than sqrt(N), then the other must be smaller. That could lead us to an improved scheme in simpleIsPrime2.
simpleIsPrime2 = @(N) all(mod(N,2:sqrt(N)));
For an integer of the size 2^64, now you only need to perform roughly 2^32 trial divides. Maybe we might consider the subtle improvement found in simpleIsPrime3, which avoids trial divides by the even integers greater than 2.
simpleIsPrime3 = @(N) (N == 2) || (mod(N,2) && all(mod(N,3:2:sqrt(N))));
simpleIsPrime3 needs only an approximate maximum of 2^31 trial divides even for numbers as large as uint64 can represent. While that is large, it is still generally doable on the computers we have today, even if it might be slow.
Sadly, my goals are higher than even the rather lofty limit given by UINT64 numbers. The problem of course is that a trial divide scheme, despite being 100% accurate in its assessment of primality, is a time hog. Even an O(sqrt(N)) scheme is far too slow for numbers with thousands or millions of digits. And even for a number as “small” as 1e100, a direct set of trial divides by all primes less than sqrt(1e100) would still be practically impossible, as there are roughly n/log(n) primes that do not exceed n. For an integer on the order of 1e50,
1e50/log(1e50)
It is practically impossible to perform that many divides on any computer we can make today. Can we do better? Is there some more efficient test for primality? For example, we could write a simple sieve of Eratosthenes to check each prime found not exceeding sqrt(N).
function [TF,SmallPrime] = simpleIsPrime4(N)
% simpleIsPrime3 - Sieve of Eratosthenes to identify if N is prime
% [TF,SmallPrime] = simpleIsPrime3(N)
%
% Returns true if N is prime, as well as the smallest prime factor
% of N when N is composite. If N is prime, then SmallPrime will be N.
Nroot = ceil(sqrt(N)); % ceil caters for floating point issues with the sqrt
TF = true;
SieveList = true(1,Nroot+1); SieveList(1) = false;
SmallPrime = 2;
while TF
% Find the "next" true element in SieveList
while (SmallPrime <= Nroot+1) && ~SieveList(SmallPrime)
SmallPrime = SmallPrime + 1;
end
% When we drop out of this loop, we have found the next
% small prime to check to see if it divides N, OR, we
% have gone past sqrt(N)
if SmallPrime > Nroot
% this is the case where we have now looked at all
% primes not exceeding sqrt(N), and have found none
% that divide N. This is where we will drop out to
% identify N as prime. TF is already true, so we need
% not set TF.
SmallPrime = N;
return
else
if mod(N,SmallPrime) == 0
% smallPrime does divide N, so we are done
TF = false;
return
end
% update SieveList
SieveList(SmallPrime:SmallPrime:Nroot) = false;
end
end
end
simpleIsPrime4 does indeed work reasonably well, though it is sometimes a little slower than is simpleIsPrime3, and everything is hugely faster than simpleIsPrime1.
timeit(@() simpleIsPrime1(111111111))
timeit(@() simpleIsPrime2(111111111))
timeit(@() simpleIsPrime3(111111111))
timeit(@() simpleIsPrime4(111111111))
All of those times will slow to a crawl for much larger numbers of course. And while I might find a way to subtly improve upon these codes, any improvement will be marginal in the end if I try to use any such direct approach to primality. We must look in a different direction completely to find serious gains.
At this point, I want to distinguish between two distinct classes of tests for primality of some large number. One class of test is what I might call an absolute or infallible test, one that is perfectly reliable. These are tests where if X is identified as prime/composite then we can trust the result absolutely. The tests I showed in the form of simpleIsPrime1, simpleIsPrime2, simpleIsPrime3 and aimpleIsprime4, were all 100% accurate, thus they fall into the class of infallible tests.
The second general class of test for primality is what I will call an evidentiary test. Such a test provides evidence, possibly quite strong evidence, that the given number is prime, but in some cases, it might be mistaken. I've already offered a basic example of a weak evidentiary test for primality in the form of roughness. All primes are maximally rough. And therefore, if you can identify X as being rough to some extent, this provides evidence that X is also prime, and the depth of the roughness test influences the strength of the evidence for primality. While this is generally a fairly weak test, it is a test nevertheless, and a good exclusionary test, a good way to avoid more sophisticated but time consuming tests.
These evidentiary tests all have the property that if they do identify X as being composite, then they are always correct. In the context of roughness, if X is not sufficiently rough, then X is also not prime. On the other side of the coin, if you can show X is at least (sqrt(X)+1)-rough, then it is positively prime. (I say this to suggest that some evidentiary tests for primality can be turned into truth telling tests, but that may take more effort than you can afford.) The problem is of course that is literally impossible to verify that degree of roughness for numbers with many thousands of digits.
In my next post, I'll look at the Fermat test for primality, based on Fermat's little theorem.
Share your learning starting trouble experience of Matlab.. Looking forward for more answers..
Helllo all
I write The MATLAB Blog and have covered various enhancements to MATLAB's ODE capabilities over the last couple of years. Here are a few such posts
- The new solution framework for Ordinary Differential Equations (ODEs) in MATLAB R2023b
- Faster Ordinary Differential Equations (ODEs) solvers and Sensitivity Analysis of Parameters: Introducing SUNDIALS support in MATLAB
- Solving Higher-Order ODEs in MATLAB
- Function handles are faster in MATLAB R2023a (Faster function handles led to faster ode45 and friends)
- Understanding Tolerances in Ordinary Differential Equation Solvers
Everyone in this community has deeply engaged with all of these posts and given me lots of ideas for future enhancements which I've dutifully added to our internal enhancment request database.
Because I've asked for so much in this area, I was recently asked if there's anything else we should consider in the area of ODEs. Since all my best ideas come from all of you, I'm asking here....
So. If you could ask for new and improved functionality for solving ODEs with MATLAB, what would it be and (ideally) why?
Cheers,
Mike
Something that I periodically wonder about is whether an integration with the Rubi integration rules package would improve symbolic integration in Matlab's Symbolic Toolbox. The project is open-source with an MIT-licensed, has a Mathematica implementation, and supposedly SymPy is working on an implementation. Much of my intrigue comes from this 2022 report that compared the previous version of Rubi (4.16.1) against various CAS systems, including Matlab 2021a (Mupad):
While not really an official metric for Rubi, this does "feel" similar to my experience computing symbolic integrals in Matlab Symbolic Toolbox vs Maple/Mathematica. What do y'all think?
Yesterday I had an urgent service call for MatLab tech support. The Mathworks technician on call, Ivy Ngyuen, helped fix the problem. She was very patient and I truly appreciate her efforts, which resolved the issue. Thank you.
I saw an interesting problem on a reddit math forum today. The question was to find a number (x) as close as possible to r=3.6, but the requirement is that both x and 1/x be representable in a finite number of decimal places.
The problem of course is that 3.6 = 18/5. And the problem with 18/5 has an inverse 5/18, which will not have a finite representation in decimal form.
In order for a number and its inverse to both be representable in a finite number of decimal places (using base 10) we must have it be of the form 2^p*5^q, where p and q are integer, but may be either positive or negative. If that is not clear to you intuitively, suppose we have a form
2^p*5^-q
where p and q are both positive. All you need do is multiply that number by 10^q. All this does is shift the decimal point since you are just myltiplying by powers of 10. But now the result is
2^(p+q)
and that is clearly an integer, so the original number could be represented using a finite number of digits as a decimal. The same general idea would apply if p was negative, or if both of them were negative exponents.
Now, to return to the problem at hand... We can obviously adjust the number r to be 20/5 = 4, or 16/5 = 3.2. In both cases, since the fraction is now of the desired form, we are happy. But neither of them is really close to 3.6. My goal will be to find a better approximation, but hopefully, I can avoid a horrendous amount of trial and error. It would seem the trick might be to take logs, to get us closer to a solution. That is, suppose I take logs, to the base 2?
log2(3.6)
I used log2 here because that makes the problem a little simpler, since log2(2^p)=p. Therefore we want to find a pair of integers (p,q) such that
log2(3.6) + delta = p + log2(5)*q
where delta is as close to zero as possible. Thus delta is the error in our approximation to 3.6. And since we are working in logs, delta can be viewed as a proportional error term. Again, p and q may be any integers, either positive or negative. The two cases we have seen already have (p,q) = (2,0), and (4,-1).
Do you see the general idea? The line we have is of the form
log2(3.6) = p + log2(5)*q
it represents a line in the (p,q) plane, and we want to find a point on the integer lattice (p,q) where the line passes as closely as possible.
[Xl,Yl] = meshgrid([-10:10]);
plot(Xl,Yl,'k.')
hold on
fimplicit(@(p,q) -log2(3.6) + p + log2(5)*q,[-10,10,-10,10],'g-')
plot([2 4],[0,-1],'ro')
hold off
Now, some might think in terms of orthogonal distance to the line, but really, we want the vertical distance to be minimized. Again, minimize abs(delta) in the equation:
log2(3.6) + delta = p + log2(5)*q
where p and q are integer.
Can we do that using MATLAB? The skill about about mathematics often lies in formulating a word problem, and then turning the word problem into a problem of mathematics that we know how to solve. We are almost there now. I next want to formulate this into a problem that intlinprog can solve. The problem at first is intlinprog cannot handle absolute value constraints. And the trick there is to employ slack variables, a terribly useful tool to emply on this class of problem.
Rewrite delta as:
delta = Dpos - Dneg
where Dpos and Dneg are real variables, but both are constrained to be positive.
prob = optimproblem;
p = optimvar('p',lower = -50,upper = 50,type = 'integer');
q = optimvar('q',lower = -50,upper = 50,type = 'integer');
Dpos = optimvar('Dpos',lower = 0);
Dneg = optimvar('Dneg',lower = 0);
Our goal for the ILP solver will be to minimize Dpos + Dneg now. But since they must both be positive, it solves the min absolute value objective. One of them will always be zero.
r = 3.6;
prob.Constraints = log2(r) + Dpos - Dneg == p + log2(5)*q;
prob.Objective = Dpos + Dneg;
The solve is now a simple one. I'll tell it to use intlinprog, even though it would probably figure that out by itself. (Note: if I do not tell solve which solver to use, it does use intlinprog. But it also finds the correct solution when I told it to use GA offline.)
solve(prob,solver = 'intlinprog')
The solution it finds within the bounds of +/- 50 for both p and q seems pretty good. Note that Dpos and Dneg are pretty close to zero.
2^39*5^-16
and while 3.6028979... seems like nothing special, in fact, it is of the form we want.
R = sym(2)^39*sym(5)^-16
vpa(R,100)
vpa(1/R,100)
both of those numbers are exact. If I wanted to find a better approximation to 3.6, all I need do is extend the bounds on p and q. And we can use the same solution approch for any floating point number.
Check out how these charts were made with polar axes in the Graphics and App Building blog's latest article "Polar plots with patches and surface".
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Apparently, the back end here is running 2025b, hovering over the Run button and the Executing In popup both show R2024a.
ver matlab
all(logical.empty)
Discuss!
